О’zbekiston respublikasi axborot texnologiyalari va kommunikatsiyalarini rivojlantirish vazirligi muhammad al-xorazmiy nomidagi toshkent axborot texnologiyalari universiteti
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О’ZBEKISTON RESPUBLIKASI AXBOROT TEXNOLOGIYALARI VA KOMMUNIKATSIYALARINI RIVOJLANTIRISH VAZIRLIGI MUHAMMAD AL-XORAZMIY NOMIDAGI TOSHKENT AXBOROT TEXNOLOGIYALARI UNIVERSITETI 2-amaliy topshiriq Fan : Mashinali o’qitish
Python muhitida Pandas, Keras, Tensorflow, kutubxonalaridan foydalangan holda jadval ko’rinishida berilgan ma’lumotlarni klassifikatsiya qilish. Google colab havola: https://colab.research.google.com/drive/1AwtsvdyKf_7L89LenC5jOwE34kBmSBj8 python dastrulash tilida yozilgan kod: import numpy as np
dataset = np.array([ [5, 1180,50, 2,1, 0], [6, 1490, 55,2,1, 0], [41, 1370, 60,2,1,0], [42, 2300,65, 2,1,0], [43, 2000,70, 2,1,0], [44, 1370,75, 2,1,0], [24, 2300,140, 4,2,1], [25, 2890,143, 4,2,1], [26, 2500,145, 4,3,1], [27, 2660,149, 4,3,1], [28, 2700,152, 4,3,1], [11, 1444,80, 2,1,0], [12, 1100,85, 3,1,0], [13, 1550,90, 3,1,0], [14, 1490,95, 3,1,0], [15, 1280,100, 3,1,0], [16, 1290,105,3,2,0], [17, 1880,110, 3,2,0], [45, 1990, 115,3,2,0], [46, 2050,120, 3,2,1], [47, 2150,125, 3,2,1], [21, 2220,130, 3,2,1], [22, 2100,135, 3,2,1], [34, 2380,137, 3,2,1], [29, 2500,120, 4,3,1], [30, 2900,156, 4,3,1], [31, 1990,157, 4,3,1], [32, 2600,159, 4,3,2], [33, 2700,160, 4,3,2], [19, 2890,150, 4,3,2], [35, 2690,175, 5,3,2], [36, 2400,180, 5,3,2], [37, 1940,185, 5,3,2], [38, 1870,189, 5,3,2], [39, 2100,200, 6,3,2], [40, 2330,195, 6,3,2], [6, 2790,196, 6,3,2], [7, 2600,200, 6,3,2], [9, 2280, 210,7,3,2], [10, 2790, 220,7,3,2] ]) x=np.array(dataset[:,0:5]) y=np.array(dataset[:,-1]) df=pd.DataFrame({ "Maktab ID":x[:,0], "O'quvchilar soni":x[:,1], "Bitiruvchilar soni":x[:,2], "Professor o'qituvchilar soni":x[:,3], "Binolar soni":x[:,4], "Sport Zallar soni":y[:], }) df Logistik regressiya tushunchasi. Xatoliklarni baholash. Klassifikatsiyalashni amalga oshirish. Download 148.57 Kb. Do'stlaringiz bilan baham: |
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