I am working on creating a simple Python machine learning script which will predict if loan will be approved or not based on below parameters business experience: should be greater than 7 year of founded: should be after 2015 loan: no previous or current loan If above conditions matches, then only loan will be approved. This dataset can be downloaded from this link: https://drive.google.com/file/d/1QtJ3EED7KDqJDrSHxHB6g9kc5YAfTlmF/view?usp=sharing For above data, I have below script from sklearn.linear_model import LogisticRegression import pandas as pd import numpy as np data = pd.read_csv("test2.csv") data.head() X = data[["Business Exp", "Year of Founded", "Previous/Current Loan"]] Y = data["OUTPUT"] clf = LogisticRegression() clf.fit(X, Y) test_x2 = np.array([[9, 2017, 0]]) Y_pred = clf.predict(test_x2) print(Y_pred) I am passing the test data in test_x2. Test data is if business exp is 9, year of founded is 2017 and no current/previous loan, so that means loan will be provided. So it should predict and the result should be 1 but it shows 0. Is there any issue with the code or with the dataset. As I am beginner in machine learning and still learning it so I have created this custom dataset for my own understanding. Continue reading...
