This project leverages various machine learning tools to predict the price movement of stocks.
Graph Data can also be found at: https://docs.google.com/spreadsheets/d/1h2iohG01RSHTFPjjJPyFlq6uHYE5OQvl8vNjeOhmg4k
- transform.ipynb
- Sector_Name_Calculation.ipynb
- RandomForest.ipynb
- KNN.ipynb
- NaiveBayes.ipynb
- NeuralNetwork.ipynb
- DecisionTree.ipynb
- SVM.ipynb
These files can be configured to operate either on the entire dataset or perform the analysis on various sectors by toggling the following parameters:
- check_each_sector: Perform a sector wise analysis if True
- less_columns: Use only the columns selected after Feature Selection if True
- minify: output only the precsion for buy signals, recall for sell signals and overall accuracy instead of the entire sklearn classification report if True
- print_data: prints the output as the classifier is run if True
- Graph Data and Graphs.zip