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Presendent bilan o’ragishda masalaning matematik qo’yilishi
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| bet | 7/44 | | Sana | 31.01.2024 | | Hajmi | 2,17 Mb. | | #149710 |
Bog'liq 1-ma’ruza. Berilganlarni intellektual tahliliga kirishPresendent bilan o’ragishda masalaning matematik qo’yilishi
Obyektlar to’plami berilgan bo’lib, ular o’zaro kesishmaydigan va sinflarga bo’lingan. Obyektlar ta turli toifadagi alomatlar bilan tavsiflangan bo’lib, ularning tasi interval, tasi nominal shkalalarda o’lchanadi.
Tanlanma obyektlarining sinfga tegishligining umumlashgan baholari hisoblansin.
Ficherning Iris tanlanmasi
setosa virginica versicolor
Fisher irisi
Yaproq piyola uzunligi
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Yaproq piyola kengligi
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Gulbarg uzunligi
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Gulbarg kengligi
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Iris turi
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5.1
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3.5
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1.4
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0.2
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setosa
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4.9
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3.0
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1.4
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0.2
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setosa
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4.7
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3.2
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1.3
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0.2
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setosa
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4.6
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3.1
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1.5
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0.2
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setosa
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5.0
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3.6
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1.4
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0.2
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setosa
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5.4
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3.9
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1.7
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0.4
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setosa
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4.6
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3.4
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1.4
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0.3
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setosa
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5.0
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3.4
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1.5
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0.2
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setosa
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4.4
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2.9
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1.4
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0.2
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setosa
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4.9
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3.1
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1.5
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0.1
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setosa
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5.4
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3.7
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1.5
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0.2
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setosa
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4.8
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3.4
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1.6
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0.2
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setosa
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4.8
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3.0
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1.4
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0.1
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setosa
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4.3
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3.0
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1.1
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0.1
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setosa
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5.8
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4.0
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1.2
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0.2
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setosa
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5.7
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4.4
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1.5
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0.4
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setosa
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5.4
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3.9
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1.3
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0.4
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setosa
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5.1
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3.5
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1.4
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0.3
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setosa
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5.7
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3.8
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1.7
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0.3
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setosa
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5.1
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3.8
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1.5
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0.3
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setosa
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5.4
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3.4
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1.7
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0.2
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setosa
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5.1
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3.7
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1.5
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0.4
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setosa
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4.6
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3.6
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1.0
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0.2
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setosa
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5.1
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3.3
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1.7
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0.5
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setosa
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4.8
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3.4
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1.9
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0.2
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setosa
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5.0
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3.0
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1.6
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0.2
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setosa
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5.0
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3.4
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1.6
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0.4
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setosa
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5.2
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3.5
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1.5
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0.2
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setosa
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5.2
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3.4
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1.4
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0.2
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setosa
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4.7
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3.2
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1.6
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0.2
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setosa
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4.8
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3.1
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1.6
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0.2
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setosa
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5.4
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3.4
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1.5
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0.4
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setosa
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5.2
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4.1
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1.5
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0.1
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setosa
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5.5
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4.2
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1.4
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0.2
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setosa
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4.9
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3.1
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1.5
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0.2
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setosa
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5.0
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3.2
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1.2
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0.2
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setosa
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5.5
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3.5
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1.3
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0.2
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setosa
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4.9
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3.6
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1.4
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0.1
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setosa
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4.4
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3.0
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1.3
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0.2
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setosa
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5.1
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3.4
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1.5
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0.2
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setosa
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5.0
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3.5
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1.3
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0.3
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setosa
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4.5
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2.3
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1.3
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0.3
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setosa
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4.4
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3.2
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1.3
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0.2
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setosa
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5.0
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3.5
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1.6
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0.6
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setosa
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5.1
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3.8
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1.9
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0.4
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setosa
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4.8
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3.0
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1.4
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0.3
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setosa
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5.1
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3.8
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1.6
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0.2
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setosa
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4.6
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3.2
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1.4
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0.2
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setosa
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5.3
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3.7
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1.5
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0.2
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setosa
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5.0
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3.3
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1.4
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0.2
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setosa
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7.0
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3.2
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4.7
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1.4
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versicolor
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6.4
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3.2
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4.5
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1.5
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versicolor
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6.9
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3.1
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4.9
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1.5
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versicolor
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5.5
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2.3
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4.0
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1.3
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versicolor
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6.5
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2.8
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4.6
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1.5
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versicolor
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5.7
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2.8
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4.5
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1.3
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versicolor
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6.3
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3.3
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4.7
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1.6
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versicolor
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4.9
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2.4
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3.3
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1.0
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versicolor
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6.6
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2.9
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4.6
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1.3
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versicolor
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5.2
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2.7
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3.9
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1.4
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versicolor
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5.0
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2.0
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3.5
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1.0
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versicolor
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5.9
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3.0
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4.2
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1.5
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versicolor
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6.0
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2.2
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4.0
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1.0
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versicolor
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6.1
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2.9
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4.7
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1.4
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versicolor
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5.6
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2.9
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3.6
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1.3
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versicolor
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6.7
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3.1
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4.4
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1.4
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versicolor
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5.6
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3.0
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4.5
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1.5
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versicolor
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5.8
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2.7
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4.1
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1.0
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versicolor
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6.2
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2.2
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4.5
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1.5
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versicolor
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5.6
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2.5
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3.9
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1.1
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versicolor
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5.9
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3.2
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4.8
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1.8
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versicolor
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6.1
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2.8
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4.0
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1.3
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versicolor
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6.3
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2.5
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4.9
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1.5
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versicolor
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6.1
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2.8
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4.7
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1.2
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versicolor
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6.4
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2.9
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4.3
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1.3
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versicolor
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6.6
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3.0
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4.4
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1.4
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versicolor
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6.8
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2.8
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4.8
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1.4
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versicolor
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6.7
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3.0
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5.0
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1.7
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versicolor
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6.0
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2.9
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4.5
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1.5
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versicolor
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5.7
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2.6
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3.5
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1.0
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versicolor
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5.5
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2.4
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3.8
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1.1
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versicolor
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5.5
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2.4
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3.7
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1.0
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versicolor
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5.8
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2.7
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3.9
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1.2
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versicolor
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6.0
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2.7
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5.1
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1.6
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versicolor
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5.4
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3.0
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4.5
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1.5
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versicolor
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6.0
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3.4
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4.5
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1.6
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versicolor
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6.7
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3.1
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4.7
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1.5
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versicolor
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6.3
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2.3
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4.4
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1.3
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versicolor
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5.6
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3.0
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4.1
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1.3
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versicolor
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5.5
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2.5
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4.0
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1.3
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versicolor
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5.5
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2.6
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4.4
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1.2
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versicolor
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6.1
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3.0
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4.6
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1.4
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versicolor
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5.8
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2.6
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4.0
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1.2
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versicolor
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5.0
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2.3
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3.3
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1.0
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versicolor
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5.6
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2.7
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4.2
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1.3
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versicolor
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5.7
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3.0
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4.2
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1.2
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versicolor
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5.7
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2.9
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4.2
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1.3
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versicolor
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6.2
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2.9
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4.3
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1.3
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versicolor
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5.1
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2.5
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3.0
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1.1
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versicolor
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5.7
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2.8
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4.1
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1.3
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versicolor
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6.3
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3.3
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6.0
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2.5
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virginica
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5.8
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2.7
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5.1
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1.9
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virginica
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7.1
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3.0
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5.9
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2.1
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virginica
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6.3
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2.9
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5.6
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1.8
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virginica
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6.5
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3.0
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5.8
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2.2
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virginica
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7.6
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3.0
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6.6
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2.1
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virginica
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4.9
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2.5
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4.5
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1.7
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virginica
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7.3
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2.9
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6.3
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1.8
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virginica
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6.7
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2.5
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5.8
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1.8
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virginica
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7.2
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3.6
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6.1
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2.5
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virginica
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6.5
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3.2
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5.1
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2.0
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virginica
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6.4
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2.7
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5.3
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1.9
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virginica
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6.8
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3.0
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5.5
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2.1
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virginica
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5.7
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2.5
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5.0
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2.0
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virginica
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5.8
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2.8
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5.1
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2.4
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virginica
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6.4
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3.2
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5.3
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2.3
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virginica
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6.5
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3.0
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5.5
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1.8
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virginica
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7.7
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3.8
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6.7
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2.2
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virginica
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7.7
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2.6
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6.9
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2.3
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virginica
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6.0
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2.2
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5.0
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1.5
|
virginica
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6.9
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3.2
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5.7
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2.3
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virginica
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5.6
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2.8
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4.9
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2.0
|
virginica
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7.7
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2.8
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6.7
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2.0
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virginica
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6.3
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2.7
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4.9
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1.8
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virginica
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6.7
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3.3
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5.7
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2.1
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virginica
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7.2
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3.2
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6.0
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1.8
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virginica
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6.2
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2.8
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4.8
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1.8
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virginica
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6.1
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3.0
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4.9
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1.8
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virginica
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6.4
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2.8
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5.6
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2.1
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virginica
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7.2
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3.0
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5.8
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1.6
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virginica
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7.4
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2.8
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6.1
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1.9
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virginica
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7.9
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3.8
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6.4
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2.0
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virginica
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6.4
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2.8
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5.6
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2.2
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virginica
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6.3
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2.8
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5.1
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1.5
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virginica
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6.1
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2.6
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5.6
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1.4
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virginica
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7.7
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3.0
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6.1
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2.3
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virginica
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6.3
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3.4
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5.6
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2.4
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virginica
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6.4
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3.1
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5.5
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1.8
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virginica
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6.0
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3.0
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4.8
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1.8
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virginica
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6.9
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3.1
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5.4
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2.1
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virginica
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6.7
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3.1
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5.6
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2.4
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virginica
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6.9
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3.1
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5.1
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2.3
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virginica
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5.8
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2.7
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5.1
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1.9
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virginica
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6.8
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3.2
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5.9
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2.3
|
virginica
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6.7
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3.3
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5.7
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2.5
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virginica
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6.7
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3.0
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5.2
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2.3
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virginica
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6.3
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2.5
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5.0
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1.9
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virginica
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6.5
|
3.0
|
5.2
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2.0
|
virginica
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6.2
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3.4
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5.4
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2.3
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virginica
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5.9
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3.0
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5.1
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1.8
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virginica
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3: Ma’ruza. Taksonomiya usullari va tajriba berilganlarini boshlang‘ich tahlili
Klasterli tahlil (cluster analysis) – berilganlarni to‘plash, tanlov obyektlari haqidagi ma’lumotlarni saqlovchi va ularni bir jinsli guruhlarga nisbatan tartiblashni bajaruvchi ko‘p o‘lchamli statistik protseduradir. Klasterizatsiya masalalari “o‘qituvchisiz o‘rgatish” masalalari sinfiga kiradi.
Klasterli tahlil quyidagi asosiy vazifalarni bajaradi:
Turlarga ajratish yoki klassifikatsiyani qayta o‘tkazish;
Obyektlarni guruhlash uchun foydali konseptual sxemalar tadqiqoti;
Berilganlarni tadqiq qilish asosida gipotezalar topish;
Gipotezalarni tekshirish.
Klasterizatsiyaning maqsadi:
Berilganlarni klasterli strukturasini aniqlash orqali tushunish.
Tanlovni o‘xshash obyektlar guruhlariga ajratish va keyingi qadamda berilganlarga ishlov berish va qaror qabul qilishni osonlashtiradi. YA’ni, har bir klasterga mos tahlil usuli qo‘llaniladi (“ajratib ol va hukmronlik qil” strategiyasi).
Berilganlarni hajmini qisqartirish. Agar tanlov keragidan ortiq katta bo‘lsa, har bir klasterdan 1 tadan, eng katta o‘xshash vakil qoldiriladi.
Yangiliklarni aniqlash (novelty detection). Hech qaysi bir klasterga kirmaydigan guruhlanmagan obyektlarni ajratib olinadi.
Yuqorida qayd qilingan masalalar quyidagi holatlarda hal qilinadi:
Klasterlar sonini kamaytirishga harakat qilinadi;
Har bir klaster ichida obyektlar o‘xshashligi eng yuqori darajada bo‘lishi muhim, klasterlar soni istagancha bo‘lishi mumkin;
Eng katta e’tibor hech bir klasterga kirmaydigan obyektlarga qaratiladi.
Bu barcha holatda iyerarxik klasterizatsiya qo‘llash mumkin, ya’ni, katta klasterlar kichik klasterlarga, kichik klasterlar o‘z navbatida yana ham kichikroq klasterlarga va h.k. ajratilishi mumkin.
Bunday masalalar taksonomiya masalalari deyiladi. Taksonomiyaning natijasi daraxt ko‘rinishidagi iyerarxik struktura bo‘ladi.
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