Optimalflow

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* Added SearchinSpace settings page in Web App. Users could custom set estimators/regressors' parameters for optimal tuning outputs.
* Modified some layouts of existing pages in Web App.

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* Created a Web App, based on flask framework, as OptimalFlow's GUI. Users could build Automated Machine Learning workflow all clicks, without any coding at all!
* Web App included PCTE workflow bulder, LogsViewer, Visualization, Documentation sections.
* Fix the filename issues in autoViz module, and remove auto_open function when generating new html format plots.

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* Modify autoPP's default_parameters: Remove "None" in "scaler", modify "sparsity" : [0.50], modify "cols" : [100]
* Modify autoViz clf_table_report()'s coloring settings
* Fix bugs in autoViz reg_table_report()'s gradient coloring function

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* Remove evaluate_model() function's round() bugs in coping with classification problem
* Move out SVM based algorithm from fastClassifier & fastRegressor's default estimators settings
* Move out SVM based algorithm from autoFS class's default selectors settings

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* Fix evaluate_model() function's bugs in coping with regression problem
* Add reg_table_report() function to create dynamic table report for regression problem in autoViz

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* Fix evaluate_model() function's precision_score issue when running modelmulti-class classification problems
* Add custom_selectors args for customized algorithm settings with autoFS's 2 classes(dynaFS_reg, dynaFS_clf)