diff --git a/abanin_daniil_lab_5/README.md b/abanin_daniil_lab_5/README.md new file mode 100644 index 0000000..2f27465 --- /dev/null +++ b/abanin_daniil_lab_5/README.md @@ -0,0 +1,38 @@ +## Лабораторная работа №5 + +### Ранжирование признаков + +## ПИбд-41 Абанин Даниил + +### Как запустить лабораторную работу: + +* установить python, pandas, matplotlib, sklearn +* запустить проект (стартовая точка lab4) + +### Какие технологии использовались: + +* Язык программирования `Python`, библиотеки pandas, matplotlib, sklearn +* Среда разработки `PyCharm` + +### Что делает лабораторная работа: +Программа решает задачу регрессии, используя полиномиальную регрессию. +Цель - предсказать сумму займа (LoanAmount), используя имеющиеся признаки: ApplicantIncome - доход заявителя, Credit_History - статус соответствия кредитной истории стандартам банка, +Education - наличие образования, Married - заявитель женат/замужем (Да/Нет), Self_Employed - самозанятый (Да/Нет) + +### Тест +Зелёные маркеры на графике - тестовые результаты +Красные маркеры на графике - предсказанные результаты + +При небольшом объёме тестовых данных, алгоритм показывает неплохие результаты обучения + +![Result](grade_1.png) + +![Result](result_1.png) + +Но при увеличении объёма данных, алгоритм теряет свою эффективность + +![Result](grade_2.png) + +![Result](result_2.png) + +Вывод: На малых объёмах данных алгоритм показывает свою эффективность. Но при большем объём стоит использовать другие методы для данного набора информации \ No newline at end of file diff --git a/abanin_daniil_lab_5/grade_1.png b/abanin_daniil_lab_5/grade_1.png new file mode 100644 index 0000000..3e73faf Binary files /dev/null and b/abanin_daniil_lab_5/grade_1.png differ diff --git a/abanin_daniil_lab_5/grade_2.png b/abanin_daniil_lab_5/grade_2.png new file mode 100644 index 0000000..db466b9 Binary files /dev/null and b/abanin_daniil_lab_5/grade_2.png differ diff --git a/abanin_daniil_lab_5/lab5.py b/abanin_daniil_lab_5/lab5.py new file mode 100644 index 0000000..2c28285 --- /dev/null +++ b/abanin_daniil_lab_5/lab5.py @@ -0,0 +1,33 @@ +from matplotlib import pyplot as plt +from sklearn import metrics +from sklearn.linear_model import LinearRegression +from sklearn.model_selection import train_test_split +from sklearn.preprocessing import PolynomialFeatures +from sklearn.pipeline import Pipeline +import pandas as pd + + +def start(): + data = pd.read_csv('loan.csv') + x = data[['ApplicantIncome', 'Credit_History', 'Education', 'Married', 'Self_Employed']] + y = data[['LoanAmount']] + + x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.1, random_state=42) + + poly = Pipeline([('poly', PolynomialFeatures(degree=3)), + ('linear', LinearRegression())]) + poly.fit(x_train, y_train) + + y_predicted = poly.predict(x_test) + + print('Оценка обучения:') + print(metrics.r2_score(y_test, y_predicted)) + + plt.figure(1, figsize=(16, 9)) + plt.title('Сравнение результатов обучения') + plt.scatter(x=[i for i in range(len(x_test))], y=y_test, c='green', s=5) + plt.scatter(x=[i for i in range(len(x_test))], y=y_predicted, c='red', s=5) + plt.show() + + +start() \ No newline at end of file diff --git a/abanin_daniil_lab_5/loan.csv b/abanin_daniil_lab_5/loan.csv new file mode 100644 index 0000000..4fe5a85 --- /dev/null +++ b/abanin_daniil_lab_5/loan.csv @@ -0,0 +1,615 @@ 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