AMAZON STOCK PRICE: VISUALIZATION, FORECASTING, AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI by Vivian Siahaan Rismon Hasiholan Sianipar

Author:Vivian Siahaan, Rismon Hasiholan Sianipar
Language: eng
Format: epub
Tags: Balige Publishing
Publisher: BALIGE PUBLISHING

Figure 3.45 The confusion matrix, true values versus predicted values diagram, ROC, and decision boundaries of MLP classifier with standard scaler

Figure 3.46 The learning curve, scalability, and performance of MLP classifier with standard scaler

PREDICTING DAILY RETURN USING LIGHT GRADIENT BOOSTING MACHINE

PREDICTING DAILY RETURN USING LIGHT GRADIENT BOOSTING MACHINE

Step 1

Run Light Gradient Boosting Machine (LGBM) on three feature scaling:

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lgbm = LGBMClassifier(max_depth = 20, n_estimators=500, subsample=0.8, random_state=2021)

for fc_name, value in feature_scaling.items():

X_train, X_test, y_train, y_test = value

run_model('Lightgbm Classifier', lgbm, X_train, X_test, y_train, y_test, fc_name, proba=True)

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