Merge pull request #303 from ZJUEarthData/dev/liaojunchi

feat: add RidgeRegression algorithm

geochemistrypi/data_mining/constants.py

@@ -45,6 +45,7 @@
     "Elastic Net",
     "SGD Regression",
     "BayesianRidge Regression",
+    "Ridge Regression",
     # "Bagging Regression",
     # "Decision Tree",
     # Histogram-based Gradient Boosting,

geochemistrypi/data_mining/model/func/algo_regression/_ridge_regression.py

@@ -0,0 +1,39 @@
+# -*- coding: utf-8 -*-
+from typing import Dict
+
+from rich import print
+
+from ....constants import SECTION
+from ....data.data_readiness import bool_input, float_input, num_input
+
+
+def ridge_regression_manual_hyper_parameters() -> Dict:
+    """Manually set hyperparameters.
+
+    Returns
+    -------
+    hyper_parameters : dict
+    """
+    print("Alpha: This hyperparameter represents the coefficient of the norm, which controls the degree of contraction constraint.")
+    print("Please indicate the coefficient of alpha. A good starting range could be between 0.001 and 2, such as 1.")
+    alpha = float_input(0.01, SECTION[2], "@Alpha: ")
+    print("Fit Intercept: This hyperparameter represents whether the model is evaluated with constant terms.")
+    print("Please indicate whether there is a parameter entry. It is generally recommended to leave it set to True.")
+    fit_intercept = bool_input(SECTION[2])
+    print("Max Iter: This hyperparameter represents the maximum number of iterations for the solver to converge.")
+    print("Please indicate the maximum number of iterations. A good starting range could be between 1000 and 10000, such as 1000.")
+    max_iter = num_input(SECTION[2], "@Max Iter: ")
+    print("Tolerance: This hyperparameter represents the tolerance of the optimization method.")
+    print("Please indicate the tolerance. A good starting range could be between 0.0001 and 0.001, such as 0.0001.")
+    tol = float_input(0.0001, SECTION[2], "@Tolerance: ")
+    # print("Selection: This hyperparameter represents the method of selecting the regularization coefficient.")
+    # print("Please indicate the method of selecting the regularization coefficient. It is generally recommended to leave it set to 'cyclic'.")
+    # selections = ["cyclic", "random"]
+    # selection = str_input(selections, SECTION[2])
+    hyper_parameters = {
+        "alpha": alpha,
+        "fit_intercept": fit_intercept,
+        "max_iter": max_iter,
+        "tol": tol,
+    }
+    return hyper_parameters