Fun Q: A Functional Introduction to Machine Learning in Q
clone this project and start q with any of the following:
q fun.q
q plt.q
q linreg.q
q onevsall.q
q nn.q
q kmeans.q
q knn.q
q recommend.q
q decisiontree.q
q adaboost.q
q randomforest.q
q supportvectormachine.q
q hiragana.q
you can then read the comments and run the examples one by one. topics include:
Binary Classification Evaluation Metrics
One vs All Logistic Regression
K-Means/Medians Clustering
Hierarchical Clustering Analysis (HCA)
Expectation Maximization (EM)
K-Nearest Neighbors (kNN)
Markov Clustering Algorithm (MCL)
Google PageRank
Content-Based Filtering (Recommender Systems)
Collaborative Filtering (Recommender Systems)
Vector Space Model (tf-idf)
Support Vector Machine (SVM)