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Experiment design

• Support input random state to split dataset

Experiment list

• Use reward metric in visualmap of hyperparams line chart(Fix bug)

Other

• Update hypergbm to 0.2.2

This release add following new features:

Dataset manage

• Search
• Delete
• Upload or import CSV
  • Sampling analysis
  • Support no column headers
  • Inferring feature types

Dataset preview

• Cat origin file on line
• Scrolling

Dataset insight

• Distribution of feature type
• Data type, feature type, missing percentage, uniques, linear correlation
• Recognize Id-ness, constant, missing percentage too high features
• Feature search
• Datetime features
  • Display by year, month, day, hour, week
• Categorical features
  • Distribution of values
  • Mode
• Continuous features
  • Distribution of interval
  • Distribution of values
  • max, min, median, mean, stand deviation

Experiment design

• Recommend experiment options
• HyperGBM,HyperDT as experiment engine
• Quick, performance training mode
• Train-Validation-Holdout data partition
• Split data in datetime order
• Support binary classification, multi-classification, regression

Experiment list

• Training process,
• Remaining time estimation
• Confusion matrix and ROC curve for binary-classification
• Evaluation metrics
  • Binary classification： Accuracy, F1, Fbeta, Precision, Recall, AUC, Log Loss
  • Multi-classification： Accuracy, F1, Fbeta, Precision, Recall, Log Loss
  • Regression： EVS, MAE, MSE, RMSE, MSLE, R2, MedianAE
• View train log and source code
• Export to notebook
• Hyper-params
• Batch predict