API Reference

CaML Core

from caml import *

CamlCATE The CamlCATE class represents an opinionated implementation of Causal Machine Learning techniques for estimating

Synthetic Data Generation

from caml.extensions.synthetic_data import *

make_partially_linear_dataset_simple Simulate data generating process from a partially linear model with a simple 1 or 2 dimensional CATE function. The outcome is continuous and the treatment can be binary or continuous.
make_partially_linear_dataset_constant Simulate a data generating process from a partially linear model with a constant treatment effect (ATE only). The outcome and treatment are both continuous.
make_fully_heterogeneous_dataset Simulate data generating process from an interactive regression model with fully heterogenous treatment effects. The outcome is continuous and the treatment is binary.
make_dowhy_linear_dataset Simulate a linear data generating process with flexible configurations. The outcome and treatment can take on different data types.

Plots

from caml.extensions.plots import *

extensions.plots.plot A plot.

Developer Tools

utils.generate_random_string Function to generate a random string of ascii lowercase letters and digits of length N.
logging.setup_logging Set up logging configuration.
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