neural network algorithm including following components
layers: conv1d, conv2d, mean pool, max pool, drop out, batch normalization, rnn, flatten, dense, tanh, relu
loss: binary crossentropy, categorical crossentropy, mse, categorical_hinge

perceptron algorithm

pocket algorithm

logistic regression algorithm including gradient descent, newton

softmax regression algorithm

learning vector quantization algorithm

k-NearestNeighbor algorithm

gaussian discriminant analysis algorithm

support vector machine algorithm including following components
kernel: linear, rbf
solver: smo, quadratic programming

discrete adaboost algorithm

real adaboost algorithm

gentle adaboost algorithm

naive bayesian algorithm for text classification

decision tree id3 algorithm

decision tree c45 algorithm

linear regression algorithm including gradient descent, newton, equation

locally weight linear regression algorithm

collaborative filtering algorithm

rbf network algorithm

decision tree cart algorithm

random_forest algorithm including bagging, random features, oob verification, feature selection

gradient boost decision tree algorithm

linear discriminant analysis algorithm with "eigen" solver

k-means algorithm

k-means++ algorithm

bisecting k-means algorithm

k-median algorithm

k-mediods algorithm

fuzzy c means algorithm

gaussian mixed model algorithm

agnes clustering algorithm

diana clustering algorithm

dbscan clustering algorithm

spectral clustering algorithm

principal Component Analysis algorithm including whiten, zero-phase component analysis whiten, kernel pca

mltidimensional scaling algorithm

locally linear embedding algorithm

support vector data description algorithm

isolate forest algorithm

independent component analysis algorithm

image preprocess algorithms including rgb2gray, histogram of oriented gradient

text preprocess algorithms including tf-idf

distance algorithms including euclidean distance, manhattan distance, chebyshev distance, mahalanobis distance, cosine distance

kernel function including linear, rbf

preprocess algorithm including min-max scaler, z-score scaler, one-hot encoder, bagging

regularizer algorithm including L1, L2, elastic-net

scores including accuracy, precision, recall, f-score, R2 score, confusion matrix, pr curve, roc curve, auc, silhouette coefficient, 2d feature scatter, learning curve, information value

optimizer algorithm including following components
gradient descent: momentum，nesterov, adagrad，rmsprop，adam

weights initialization algorithm