├── .gitignore ├── .travis.yml ├── Dockerfile ├── LICENSE.md ├── README.md ├── base ├── arff.go ├── arff_test.go ├── attributes.go ├── attributes_test.go ├── bag.go ├── bag_test.go ├── binary.go ├── categorical.go ├── classifier.go ├── conversion.go ├── csv.go ├── csv_test.go ├── data.go ├── dataframe_go.go ├── dense.go ├── dense_test.go ├── domain.go ├── error.go ├── error_test.go ├── filewrapper.go ├── filtered.go ├── filters.go ├── fixed.go ├── float.go ├── group.go ├── lazy_sort_test.go ├── logger.go ├── mat.go ├── mat_test.go ├── serialize.go ├── serialize_attributes.go ├── serialize_instances.go ├── serialize_test.go ├── sort.go ├── sort_test.go ├── spec.go ├── util.go ├── util_attributes.go ├── util_instances.go ├── util_test.go ├── view.go └── view_test.go ├── clustering ├── cluster_extra_test.go ├── cluster_test.go ├── clustering.go ├── dbscan.csv ├── dbscan.go ├── dbscan_labels.csv ├── dbscan_test.go ├── em.go ├── em_test.go ├── gaussian_mixture.csv ├── gaussian_mixture.py ├── gaussian_mixture_labels.csv ├── gaussian_mixture_single_obs.csv ├── gen_test.py └── synthetic.csv ├── coverage.sh ├── doc ├── zh_CN │ ├── AddingAttributes.md │ ├── AttributeSpecifications.md │ ├── CSVFiles.md │ ├── Classification │ │ ├── KNN.md │ │ ├── Regression.md │ │ ├── Trees.md │ │ └── liblinear.md │ ├── Contributing.md │ ├── CustomDataGrids.md │ ├── Filtering.md │ ├── FloatAttributePrecision.md │ ├── Home.md │ ├── Installation.md │ └── Instances.md └── zh_TW │ ├── AddingAttributes.md │ ├── AttributeSpecifications.md │ ├── CSVFiles.md │ ├── Classification │ ├── KNN.md │ ├── Regression.md │ ├── Trees.md │ └── liblinear.md │ ├── Contributing.md │ ├── CustomDataGrids.md │ ├── Filtering.md │ ├── FloatAttributePrecision.md │ ├── Home.md │ ├── Installation.md │ └── Instances.md ├── ensemble ├── ensemble.go ├── multisvc.go ├── multisvc_test.go ├── randomforest.go └── randomforest_test.go ├── evaluation ├── confusion.go ├── confusion_test.go ├── cross_fold.go └── cross_fold_test.go ├── examples ├── averageperceptron │ └── averageperceptionexample.go ├── crossfold │ └── rf.go ├── datasets │ ├── articles.csv │ ├── boston_house_prices.csv │ ├── c45-numeric.csv │ ├── chim.csv │ ├── exam.csv │ ├── exams.csv │ ├── gaussian_outliers.csv │ ├── house-votes-84.csv │ ├── iris.arff │ ├── iris.csv │ ├── iris_binned.csv │ ├── iris_headers.csv │ ├── iris_headers_subset.csv │ ├── iris_sorted_asc.csv │ ├── iris_sorted_desc.csv │ ├── mnist_test.csv │ ├── mnist_train.csv │ ├── randomdata.csv │ ├── sources.txt │ ├── tennis.csv │ ├── titanic.csv │ └── weather.arff ├── instances │ └── instances.go ├── knnclassifier │ └── knnclassifier_iris.go ├── serialization │ └── attributes.go └── trees │ ├── cart │ └── cart.go │ ├── id3 │ └── trees.go │ └── isolationForest │ └── isolation_forest.go ├── filters ├── binary.go ├── binary_test.csv ├── binary_test.go ├── binning.go ├── binning_test.go ├── chimerge.go ├── chimerge_freq.go ├── chimerge_funcs.go ├── chimerge_test.go ├── disc.go ├── float.go └── float_test.go ├── go.mod ├── go.sum ├── golearn.go ├── kdtree ├── heap.go ├── heap_test.go ├── kdtree.go └── kdtree_test.go ├── knn ├── euclidean.c ├── knn.go ├── knn.h ├── knn_bench_test.go ├── knn_cov_test.go ├── knn_kdtree_test.go ├── knn_opt_euclidean.go ├── knn_test.go ├── knn_test_1.csv ├── knn_test_2.csv ├── knn_test_2_subset.csv ├── knn_train_1.csv ├── knn_train_2.csv ├── knn_weighted_test.go └── temp.cls ├── linear_models ├── blas.h ├── blasp.h ├── cfuncs.go ├── daxpy.c ├── ddot.c ├── dnrm2.c ├── doc.go ├── dscal.c ├── liblinear.go ├── liblinear_print.go ├── liblinear_print_11.go ├── linear.cpp ├── linear.h ├── linear_models_test.go ├── linear_regression.go ├── linear_regression_test.go ├── linearsvc.go ├── linearsvc_test.go ├── logistic.go ├── logistic_test.go ├── test.csv ├── tmp ├── train.csv ├── tron.cpp ├── tron.h └── util.go ├── meta ├── bagging.go ├── bagging_test.go ├── meta.go ├── one_v_all.go └── one_v_all_test.go ├── metrics └── pairwise │ ├── chebyshev.go │ ├── chebyshev_test.go │ ├── cosine.go │ ├── cosine_test.go │ ├── cranberra.go │ ├── cranberra_test.go │ ├── euclidean.go │ ├── euclidean_test.go │ ├── manhattan.go │ ├── manhattan_test.go │ ├── pairwise.go │ ├── poly_kernel.go │ ├── poly_kernel_test.go │ ├── rbf_kernel.go │ └── rbf_kernel_test.go ├── naive ├── bernoulli_nb.go ├── bernoulli_nb_test.go ├── naive.go └── test │ ├── simple_test.csv │ └── simple_train.csv ├── neural ├── funcs.go ├── layered.go ├── layered_test.go ├── network.go ├── network_test.go ├── neural.go └── xor.csv ├── optimisation └── optimisation.go ├── pca ├── pca.go └── pca_test.go ├── perceptron ├── average.go └── average_test.go ├── trees ├── benchdata.csv ├── cart_classifier.go ├── cart_regressor.go ├── cart_test.go ├── cart_utils.go ├── entropy.go ├── gini.go ├── gr.go ├── id3.go ├── id3_test.go ├── isolation.go ├── isolation_test.go ├── onerow.csv ├── random.go ├── sorter.go ├── tree_bench_test.go ├── tree_test.go └── trees.go └── utilities 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