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