.

plots.py

@@ -2,6 +2,8 @@ import numpy as np
 import matplotlib.pyplot as plt
 import pandas as pd
 import seaborn as sns
+from sklearn.metrics import mean_absolute_error
+
 
 sns.set_theme()
 
@@ -64,36 +66,115 @@ def plot_distribution(preds_values, actual_values, mae_values, model_name, thres
         plt.close()
 
 
-if __name__ == "__main__":
-    preds_values, actual_values, mae_values = read_results("linear_models/lasso_0.01_0.99.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "Lasso", [0.01, 0.99], False)
-
-    preds_values, actual_values, mae_values = read_results("linear_models/lin_reg_0.01_0.99.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "Linear regression", [0.01, 0.99], False)
-
-    preds_values, actual_values, mae_values = read_results("linear_models/sgd_reg_0.01_0.99.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "SGD Regressor", [0.01, 0.99], False)
-
-    preds_values, actual_values, mae_values = read_results("oversampled_False_catboost_reg_0.01_0.99.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "CatBoostRegressor", [0.01, 0.99], False)
-
-    preds_values, actual_values, mae_values = read_results("linear_models/lasso_0.2_0.8.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "Lasso", [0.2, 0.8], False)
+def print_category_errors(actual, preds):
+    for i in range(2):
+        if i == 0:
+            input_type = "BoW"
+        else:
+            input_type = "TF-IDF"
 
-    preds_values, actual_values, mae_values = read_results("linear_models/oversampled_lin_reg_0.01_0.99.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "Linear regression", [0.01, 0.99], True)
+        preds = preds_values[i]
+        actual = actual_values[i]
+        mae = mae_values[i]
 
-    preds_values, actual_values, mae_values = read_results("linear_models/oversampled_lasso_0.01_0.99.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "Lasso", [0.01, 0.99], True)
+        print(input_type)
+        actual1 = list(actual[np.where(actual < 0.98)])
+        preds1 = list(preds[np.where(actual < 0.98)])
+        print(f"Category 1 MAE: {mean_absolute_error(actual1, preds1):.4f}")
+        print(f"Category 1 correlation: {np.corrcoef(actual1, preds1)[0][1]:.4f}")
+        print()
+
+        actual2 = list(actual[np.where((actual >= 0.98) & (actual < 1.5))])
+        preds2 = list(preds[np.where((actual >= 0.98) & (actual < 1.5))])
+        print(f"Category 2 MAE: {mean_absolute_error(actual2, preds2):.4f}")
+        print(f"Category 2 correlation: {np.corrcoef(actual2, preds2)[0][1]:.4f}")
+        print()
+
+        actual3 = list(actual[np.where((actual >= 1.5) & (actual < 2))])
+        preds3 = list(preds[np.where((actual >= 1.5) & (actual < 2))])
+        print(f"Category 3 MAE: {mean_absolute_error(actual3, preds3):.4f}")
+        print(f"Category 3 correlation: {np.corrcoef(actual3, preds3)[0][1]:.4f}")
+        print()
+
+        actual4 = list(actual[np.where(actual >= 2)])
+        preds4 = list(preds[np.where(actual >= 2)])
+        print(f"Category 4 MAE: {mean_absolute_error(actual4, preds4):.4f}")
+        print(f"Category 4 correlation: {np.corrcoef(actual4, preds4)[0][1]:.4f}")
+        print()
+        print(f"Overall corr: {np.corrcoef(actual, preds)[0][1]:.4f}")
 
-    preds_values, actual_values, mae_values = read_results("linear_models/oversampled_sgd_reg_0.01_0.99.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "SGD Regressor", [0.01, 0.99], True)
 
-    preds_values, actual_values, mae_values = read_results("oversampled_True_catboost_reg_0.01_0.99.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "CatBoostRegressor", [0.01, 0.99], True)
+if __name__ == "__main__":
+    filename = "linear_models/lasso_0.01_0.99.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "Lasso", [0.01, 0.99], False)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "linear_models/lin_reg_0.01_0.99.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "Linear regression", [0.01, 0.99], False)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "linear_models/sgd_reg_0.01_0.99.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "SGD Regressor", [0.01, 0.99], False)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "oversampled_False_catboost_reg_0.01_0.99.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "CatBoostRegressor", [0.01, 0.99], False)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "linear_models/lasso_0.2_0.8.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "Lasso", [0.2, 0.8], False)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "linear_models/oversampled_lin_reg_0.01_0.99.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "Linear regression", [0.01, 0.99], True)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "linear_models/oversampled_lasso_0.01_0.99.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "Lasso", [0.01, 0.99], True)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "linear_models/oversampled_sgd_reg_0.01_0.99.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "SGD Regressor", [0.01, 0.99], True)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "oversampled_True_catboost_reg_0.01_0.99.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "CatBoostRegressor", [0.01, 0.99], True)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
+
+    filename = "linear_models/oversampled_lasso_0.15_0.85.txt"
+    print(filename)
+    preds_values, actual_values, mae_values = read_results(filename)
+    #plot_distribution(preds_values, actual_values, mae_values, "Lasso", [0.15, 0.85], True)
+    print_category_errors(actual_values, preds_values)
+    print("============================")
 
-    preds_values, actual_values, mae_values = read_results("linear_models/oversampled_lasso_0.15_0.85.txt")
-    plot_distribution(preds_values, actual_values, mae_values, "Lasso", [0.15, 0.85], True)