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Tasks:\n"\n"\n Implement polynomial features [10p]\n"\n* Implement minmax normalisation [10p]\n"\n* Implement logistic regression loss function and gradient descent algorithm [10p]\n"\n* Plot learning and test curve [10p]\n"\n* Generate test prediction (test dataset) [10p]\n"\n* Fill the confusion matrix (test dataset) [10p]\n"\n* Compute F1 score, precision, recall and accuracy using confusion matrix (test dataset) [10p]\n"\n* Try various learning rate and compute F1 score of each learning rate (test dataset) [10p]\n"\n* Learning rates: (0.0001, 0.0005, 0.0007, 0.001, 0.005, 0.001, 0.01, 0.05, 0.09, 0.1, 0.4, 0.7) [10p]\n"\n* Generate the lists for each learning rate and its associated F1 score and plot (test dataset) [10p]

          ***Tasks:**\n"\n"\n* Implement polynomial features [10p]\n"\n* Implement minmax normalisation [10p]\n"\n* Implement logistic regression loss function and gradient descent algorithm [10p]\n"\n* Plot learning and test curve [10p]\n"\n* Generate test prediction (test dataset) [10p]\n"\n* Fill the confusion matrix (test dataset) [10p]\n"\n* Compute F1 score, precision, recall and accuracy using confusion matrix (test dataset) [10p]\n"\n* Try various learning rate and compute F1 score of each learning rate (test dataset) [10p]\n"\n* Learning rates: (0.0001, 0.0005, 0.0007, 0.001, 0.005, 0.001, 0.01, 0.05, 0.09, 0.1, 0.4, 0.7) [10p]\n"\n* Generate the lists for each learning rate and its associated F1 score and plot (test dataset) [10p]

***Tasks:**""* Implement polynomial features [10p]"* Implement minmax normalisation [10p]"* Implement logistic regression loss function and gradient descent algorithm [10p]"* Plot learning and test curve [10p]"* Generate test prediction (test dataset) [10p]"* Fill the confusion matrix (test dataset) [10p]"* Compute F1 score, precision, recall and accuracy using confusion matrix (test dataset) [10p]"* Try various learning rate and compute F1 score of each learning rate (test dataset) [10p]"* Learning rates: (0.0001, 0.0005, 0.0007, 0.001, 0.005, 0.001, 0.01, 0.05, 0.09, 0.1, 0.4, 0.7) [10p]"* Generate the lists for each learning rate and its associated F1 score and plot (test dataset) [10p]

Added by Martin C.

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