Install & Compatibility
Where this runs
No compatibility data collected yet for this library.
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
CTBoostClassifier
✓ from ctboost import CTBoostClassifier
✗ from ctboost import CTBoostClassifier
Quickstart example with CTBoostClassifier on synthetic data, CPU mode.
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from ctboost import CTBoostClassifier
X, y = make_classification(n_samples=1000, n_features=20, random_state=42)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
model = CTBoostClassifier(n_estimators=100, learning_rate=0.1, use_gpu=False)
model.fit(X_train, y_train)
print(f"Accuracy: {model.score(X_test, y_test):.3f}")
Debug
Known issues
deprecatedThe parameter `verbose` was renamed to `verbosity` in version 0.1.40. Using `verbose` raises a deprecation warning and will be removed in the future.fixReplace `verbose=True` with `verbosity=1` or higher.
affects: >=0.1.40, <0.1.46
breakingIn version 0.1.35, the default value of `use_gpu` changed from `False` to `None`. `None` means auto-detect GPU. Code that relied on `use_gpu=False` being default may now unexpectedly attempt GPU usage on machines with NVIDIA GPUs.fixExplicitly set `use_gpu=False` if CPU execution is required.
affects: >=0.1.35
gotchaCTBoost currently does not support missing values (NaN). Passing a DataFrame with NaN will raise an error. Pre-impute missing values before fitting.fixUse `sklearn.impute.SimpleImputer` or a similar imputation strategy.
affects: all
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Version history
0.1.50latest on PyPI · released Apr 24, 2026
Audit
Dependencies
numpyrequiredCore dependency for array operations
pandasrequiredRequired for DataFrame input handling
scipyrequiredUsed for statistical computations in CIT
numbaoptionalJIT compilation for GPU acceleration
cupyoptionalGPU arrays support when using CUDA backend