"""增强探针法因子筛选 (Probe Feature Selection)

基于噪音探针的统计显著性特征选择方法。

核心组件:
    - ProbeSelector: 主选择器，协调整个筛选流程
    - NoiseGenerator: 噪音生成器，Polars 零拷贝注入
    - ProbeTrainer: 多任务训练器，支持验证集早停
    - ImportanceEvaluator: 重要性评估器，强制 Gain
    - LightGBMClassifier: 分类模型

使用示例:
    >>> from src.experiment.probe_selection import ProbeSelector
    >>>
    >>> selector = ProbeSelector(
    ...     n_iterations=3,
    ...     n_noise_features=5,
    ...     validation_ratio=0.15,
    ... )
    >>>
    >>> selected_features = selector.select(
    ...     data=train_data,
    ...     feature_cols=all_features,
    ...     target_col_regression="future_return_5",
    ...     date_col="trade_date",
    ... )
"""

from src.experiment.probe_selection.importance_evaluator import ImportanceEvaluator
from src.experiment.probe_selection.lightgbm_classifier import LightGBMClassifier
from src.experiment.probe_selection.noise_generator import NoiseGenerator
from src.experiment.probe_selection.probe_selector import ProbeSelector
from src.experiment.probe_selection.probe_trainer import (
    ProbeTrainer,
    create_classification_target,
    split_validation_by_date,
)

__all__ = [
    "ProbeSelector",
    "NoiseGenerator",
    "ProbeTrainer",
    "ImportanceEvaluator",
    "LightGBMClassifier",
    "create_classification_target",
    "split_validation_by_date",
]