add-truera-snippet.py

! pip install truera
from truera.client.truera_workspace import TrueraWorkspace #import truera
from truera.client.truera_authentication import TokenAuthentication # import authentication
tru = TrueraWorkspace("https://app.truera.net", TokenAuthentication("ADD YOUR AUTH TOKEN")) 
tru.add_project("My project", score_type="CHOOSE A SCORE TYPE: regression, classification, probits or logits")
tru.add_data_collection("data_collection_1") # the schema that will hold your data "splits" and model
tru.add_data(
    data = data,
    data_split_name = "train",
    column_spec=ColumnSpec(
        id_col_name = "id",
        pre_data_col_names=["X1","X2"],
        label_col_names="target")
)
tru.add_python_model("model_1", my_model_object) #add python model
tru.set_data_split("train")
preds = tru.get_ys_pred().reset_index(names = "id")
tru.add_data(
    data = preds,
    data_split_name = "train",
    column_spec=ColumnSpec(
        id_col_name="id",
        prediction_col_names="prediction")
)
tru.set_influence_type("shap")
# reduce settings for speed
tru.set_num_internal_qii_samples(100)
tru.set_num_default_influences(100)
explainer = tru.get_explainer("train")
infs = explainer.get_feature_influences().reset_index(names = "id")
model_output_context = ModelOutputContext(model_name='model_1',
                                          score_type='regression',
                                          background_split_name='train',
                                          influence_type='kernel-shap')
tru.add_data(
    data = infs,
    data_split_name = "train",
    column_spec = ColumnSpec(
        id_col_name = "id",
        feature_influence_col_names = ["X1_influence","X2_influence"]),
    model_output_context=model_output_context)