+ Update documents, examples, and README + Update pre-condition check for all metrics + Remove `decimal` parameter in all metrics + Replace `non_zero`, `positive` parameters by `force_finite`, `finite_value` in many metrics. + Add features tests and comparisons tests

+ Update documents, examples, and README + Update pre-condition check for all metrics + Remove `decimal` parameter in all metrics + Replace `non_zero`, `positive` parameters by `force_finite`, `finite_value` in many metrics. + Add features tests and comparisons tests

+ Update documents, examples, and README + Update pre-condition check for all metrics + Remove `decimal` parameter in all metrics + Replace `non_zero`, `positive` parameters by `force_finite`, `finite_value` in many metrics. + Add features tests and comparisons tests

+ Update documents, examples, and README + Update pre-condition check for all metrics + Remove `decimal` parameter in all metrics + Replace `non_zero`, `positive` parameters by `force_finite`, `finite_value` in many metrics. + Add features tests and comparisons tests

+ Add metrics to ClusteringMetric class: + Mean Squared Error Index (MSEI) + Adjusted Rand Score (ARS) + Gamma Score (GAS) + Gplus Score (GPS) + Speed up all metrics in ClusteringMetric by transferring the computation to cluster_util module. + Add speed up examples for clustering metrics **(10x-100x faster than previous version)** + Update documents, ChangeLog, Readme

+ Reformat ClassificationMetric, RegressionMetric, and ClusteringMetric + Fix bugs in metrics: + ROC-AUC score + F2 score, FBeta score + Hamming Score, Accuracy Score + Add metrics to ClassificationMetric: + Brier Score Loss (BSL) + Kullback-Leibler Divergence Loss (KLDL) + Cross-Entropy Loss (CEL) + Hinge Loss (HL) + Update docs, examples

+ Fix bug in get_support() function + Fix bug rounding number in ClassificationMetric + Update logo and docs

+ Remove all lowercase shortname of all metrics + Fix bugs in GINI function belongs to ClassificationMetric + Fix bugs in some functions belong to ClusteringMetric + Update characteristics of most of the functions (valid ranges and best value) + Add metrics to ClusteringMetrics + Entropy Score (ES) + Purity Score (PuS) + Tau Score (TS) + Duda-Hart Index (DHI) + Sum of Squared Error Index (SSEI) + Beale Index (BI) + R-Squared Index (RSI) + Density-Based Clustering Validation Index (DBCVI) + Hartigan Index (HI) + Add get_support() method in RegressionMetric, ClassificationMetric, and ClusteringMetric + Update and add more examples to all classes. + Update documents for all metrics.