README.rst

gbt-regression

This app creates and fits an XGBoost Gradient Boosted Tree model based on parquet-formatted input data. The arguments to the program are as follows:

train: (str, required) local path or URI of a parquet file containing training data
test: (str, required) local path or URI of a parquet file containing test data
n-trees: (int) number of trees for the regressor; default 100
m-depth: (int) maximum depth of trees of regressor; default 10
learning-rate: (float) learning rate of the model; ranges from 0.0 to 1.0; default .2
loss: (str) name of loss function to be used; default "rmse"
label-col: (str, required) name of label column in dataset; string input
feat-cols: (str) names of columns in dataset to be used as features; input is one string with names delimited by commas. If no argument is provided, it is assumed that all columns but the label column are feature columns.

This app currently assumes that the input data is all numerical.

To run the app with default parameters while in the root directory, run the command

mlflow run apps/gbt-regression -P train="insert/data/path/" -P test="insert/data/path/" -P label-col="insert.label.col"