Loading server.py +1 −17 Original line number Diff line number Diff line Loading @@ -50,11 +50,6 @@ def correctPrediction(): # TODO make this get the actual ranking of algorithms @app.route('/getAlgorithms', methods=["GET"]) def getTopAlgorithms(): # name = ["This (in use)", "Comes", "From", "The", "Server"] # f1 = ["5", "4", "3", "2", "1"] # precision = ["1", "2", "3", "4", "5"] # recall = ["1", "2", "3", "4", "5"] # accuracy = ["1", "2", "3", "4", "5"] name = ["Perceptron", "Stochastic Gradient Descent", "Neural Network", "Decision Tree"] # accuracy, precision, recall, f1 = ml.getPerformanceMetrics() Loading @@ -63,17 +58,6 @@ def getTopAlgorithms(): precision = result[1] recall = result[2] f1 = result[3] # print(accuracy) # print(precision) # print(recall) # print(f1) # name = "test" # f1 = "test" # precision = "test" # recall = "test" # accuracy = "test" val = { "name": name, Loading Loading
server.py +1 −17 Original line number Diff line number Diff line Loading @@ -50,11 +50,6 @@ def correctPrediction(): # TODO make this get the actual ranking of algorithms @app.route('/getAlgorithms', methods=["GET"]) def getTopAlgorithms(): # name = ["This (in use)", "Comes", "From", "The", "Server"] # f1 = ["5", "4", "3", "2", "1"] # precision = ["1", "2", "3", "4", "5"] # recall = ["1", "2", "3", "4", "5"] # accuracy = ["1", "2", "3", "4", "5"] name = ["Perceptron", "Stochastic Gradient Descent", "Neural Network", "Decision Tree"] # accuracy, precision, recall, f1 = ml.getPerformanceMetrics() Loading @@ -63,17 +58,6 @@ def getTopAlgorithms(): precision = result[1] recall = result[2] f1 = result[3] # print(accuracy) # print(precision) # print(recall) # print(f1) # name = "test" # f1 = "test" # precision = "test" # recall = "test" # accuracy = "test" val = { "name": name, Loading