Fixed XGBRegressor

DisplayWindow.py

@@ -22,19 +22,6 @@ diamonds.dropna(inplace=True)
 cut = list(diamonds["cut"].unique())
 colors = list(diamonds["color"].unique())
 clarity = list(diamonds["clarity"].unique())
-# diamonds_numerical = diamonds.copy()
-# cut_mapping = {cut: i for i, cut in enumerate(diamonds['cut'].unique())}
-# color_mapping = {color: i for i, color in enumerate(diamonds['color'].unique())}
-# clarity_mapping = {clarity: i for i, clarity in enumerate(diamonds['clarity'].unique())}
-# diamonds_numerical['cut'] = diamonds['cut'].map(cut_mapping)
-# diamonds_numerical['color'] = diamonds['color'].map(color_mapping)
-# diamonds_numerical['clarity'] = diamonds['clarity'].map(clarity_mapping)
-# X = diamonds_numerical.drop('price', axis = 1)
-# y = diamonds_numerical['price']
-# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
-# model = Model(X_train, X_test, y_train, y_test,'RF')
-# model.train()
-# joblib.dump(model, 'RF.joblib')
 model = joblib.load('RF.joblib')
 price = 0
 
@@ -117,14 +104,14 @@ class MainWindow(QMainWindow):
         self.show()
 
     def update_values(self):
-
+        self.GUI_selections = {}
         for key, value in self.menu_items.items():
             if Advanced.Advanced_selections[value]:
                 if key < 3:
                     self.GUI_selections[value] = self.input_fields[key].currentText()
                 else:
                     if self.validate_inputs(self.input_fields[key].text(), value):
-                        self.GUI_selections[value] = self.input_fields[key].text()
+                        self.GUI_selections[value] = float(self.input_fields[key].text())
                     else:
                         return
 
@@ -180,8 +167,8 @@ class Advanced(QMainWindow):
         self.graph_selector_Y.addItems((self.check_labels + ['price']))
         self.regression_model.addItems(["Linear Regression", "XGBRegressor", "Neural Network",
                                         "Random Forest Regressor"])
-        self.teach = QPushButton('Re-Teach', self)
-        self.teach.clicked.connect(self.re_teach)
+        self.teach = QPushButton('Re-Train', self)
+        self.teach.clicked.connect(self.re_train)
         self.plot_graph = QPushButton('PLOT', self)
         self.plot_graph.clicked.connect(self.create_graph)
 
@@ -214,7 +201,7 @@ class Advanced(QMainWindow):
             else:
                 Advanced.Advanced_selections[checkbox.text()] = True
 
-    def re_teach(self):
+    def re_train(self):
         global diamonds
         X = diamonds.copy()
         for key, value in Advanced.Advanced_selections.items():

modeling.py

@@ -21,7 +21,7 @@ class Model:
         if self.modelname == "Linear Regression":
             self.model = LinearRegression()
         elif self.modelname == "XGBRegressor":
-            self.model = XGBRegressor(random_state=42, n_estimators=100)
+            self.model = XGBRegressor(random_state=42, n_estimators=100, enable_categorical = True)
         elif self.modelname == "Neural Network":
             self.model = MLPRegressor(random_state=42, max_iter=500)
         elif self.modelname == "Random Forest Regressor":