A Classifier for Tensorflow Boosted Trees models.

Used in the notebooks

Used in the tutorials

feature_columns An iterable containing all the feature columns used by the model. All items in the set should be instances of classes derived from FeatureColumn.
n_batches_per_layer the number of batches to collect statistics per layer. The total number of batches is total number of data divided by batch size.
model_dir Directory to save model parameters, graph and etc. This can also be used to load checkpoints from the directory into a estimator to continue training a previously saved model.
n_classes number of label classes. Default is binary classification.
weight_column A string or a NumericColumn created by tf.fc_old.numeric_column defining feature column representing weights. It is used to downweight or boost examples during training. It will be multiplied by the loss of the example. If it is a string, it is used as a key to fetch weight tensor from the features. If it is a NumericColumn, raw tensor is fetched by key weight_column.key, then weight_column.normalizer_fn is applied on it to get weight tensor.
label_vocabulary A list of strings represents possible label values. If given, labels must be string type