Release Note

Version 0.1.2

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

Version 0.1.1

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