Mashinali o’qitish fanidan 20-03 – guruh talabasi Bajardi : Bozorov B. Tekshirdi : Axrorov M
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4- bozorov lab ishi
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- Mavzu: Logistik regressiya tushunchasi va ularni mashinali o’qitishda qo’llanilishi.
- Logistic-Reggression
- MarkerFaceColorni
O’ZBEKISTON RESPUBLIKASI AXBOROT TEXNOLOGIYALARI VA KOMUNIKATSIYALARINI RIVOJLANTIRISH VAZIRLIGI Muhammad Al-Xorazmiy nomidagi Toshkent Axborot Texnologiyalari Universiteti Samarqand filiali 4-AMALIY ISHI Mavzu: Logistik regressiya tushunchasi va ularni mashinali o’qitishda qo’llanilishi. Mashinali o’qitish fanidan 20-03 – guruh talabasi Bajardi : Bozorov B. Tekshirdi : Axrorov M. Samarqand -2023 Mavzu: Logistik regressiya tushunchasi va ularni mashinali o’qitishda qo’llanilishi. Biz bu laboratoriya topshirig’ini Mathlab dasturida tayyor kutubxonalardan foydalanib vazifani bajaramiz. Men bu vazifani talabalar sessiya imtixonini topshirdimi yoki yo’qmi shu haqda tayyorladim. Ya’ni bizga ma’lumki talaba sessiya imtixoniga kirishi uchun avval fandan kamida 60 bal va sessiya imtixonida ham kamida 60 ball olsa u sessiyani topshirgan hisoblanadi. Men bu laboratoriya ishini 20 ta talaba misolida ishladim. Unda amallarni ketma – ket bajaramiz. Matlab dasturini ishga tushiramiz. (1-rasm) 1-rasm Logistik regressiya papkasini yo’lini ko’rsatamiz. (2-rasm) 2-rasm Papkani ko’rsatganimizda quyidagi ko’rinishda bo’ladi. (3-rasm) 3-rasm Logistic-Reggression papkasidan Main.m va plotdata.m fayllaridan foydalanamiz. (4-rasm) 4-rasm Data fayli qiymatlarini kamaytiramiz. (5-rasm) 5-rasm Grafik natijalarini hosil qilish uchun sichqonchaning o’ng tugmasini bosamiz. Evaluste Selection buyrug’idan foylanamamiz. (6-rasm) 6-rasm Misolimiz natijasi quyidagi grafik ko’rinishida bo’ladi. (7-rasm) 7-rasm Imtihondan o’tolmagan talabalarning belgisining rangini o’zgartirishimiz mumkin. MarkerFaceColorni red(qizil) rangga o’zgartiramiz. (8-rasm) 8-rasm ILOVA Dasturning kodi: function plotData(X, y) %PLOTDATA Plots the data points X and y into a new figure % PLOTDATA(x,y) plots the data points with + for the positive examples % and o for the negative examples. X is assumed to be a Mx2 matrix. % Create New Figure figure; hold on ; % Find Indices of Positive and Negative Examples pos = find(y==1); neg = find(y == 0); % Plot Examples plot(X(pos, 1), X(pos, 2), 'k+' , 'LineWidth' , 2, 'MarkerSize' , 7); plot(X(neg, 1), X(neg, 2), 'ko' , 'MarkerFaceColor' , 'r' , 'MarkerSize' , 7); hold off ; end FOYDALANILGAN ADABIYOTLAR: 1. MATLAB 7.*/R2006/R2007 o’quv qo’llanma. M.2008. 2. Mathematica. Wolfram, Stephen, 1959. 3. Dyakonov V. P., Abramyenkova I. V., Kruglov V. V. MATLAB 5 s pakyetami rasshiryeniy. – M.: Nolidj, 2001. 4. Dyakonov V. P. MATLAB 6.5 SP1/7 + Simulink 5/6 v. Obrabotka signalov I proyektirovaniye filtrov. – M.: Solon_R, 2005. 5. Dyakonov V. P. MATLAB 6.5 SP1/7 + Simulink 5/6 v. Rabota s izobrajye_ niyami i vidyeopotokami. – M.: Solon_R, 2005. Download 26.53 Kb. Do'stlaringiz bilan baham: |
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