class StrategyReasoner:
    def decide(self, dataset_info, problem_type):
        strategy = {}
        risks = []
        score = 0.0

        if dataset_info.get("small_data"):
            risks.append("small_dataset")
            score += 0.1

        if dataset_info.get("high_dimensional"):
            risks.append("high_dimensionality")
            score += 0.1

        if dataset_info.get("imbalance"):
            risks.append("class_imbalance")
            score += 0.2

        if dataset_info.get("sparse_data"):
            risks.append("high_missingness")
            score += 0.2

        if problem_type == "classification":
            if "small_dataset" in risks:
                model_family = "tree_ensemble"
                reason = "Small datasets benefit from simpler models"
            elif "high_dimensionality" in risks:
                model_family = "tree_ensemble"
                reason = "Tree ensembles handle high-dimensional data better"
            else:
                model_family = "tree_ensemble"
                reason = "Tree ensembles handle complexity well"

        elif problem_type == "regression":
            if "high_dimensionality" in risks:
                model_family = "tree_ensemble"
                reason = "Tree ensembles handle high-dimensional data better"
            else:
                model_family = "linear_or_tree"
                reason = "Balances interpretability and accuracy"

        elif problem_type == "nlp":
            model_family = "transformer"
            reason = "Transformers best capture language semantics"

        strategy["model_family"] = model_family
        strategy["reason"] = reason
        strategy["risks"] = risks
        strategy["confidence"] = round(1 - min(score, 0.9), 2)

        return strategy

    def explain_strategy(self, strategy):
        explanation = f"Selected {strategy['model_family']} models because: {strategy['reason']}."
        if strategy.get("risks"):
            explanation += f" Identified risks: {', '.join(strategy['risks'])}."
        return explanation

    def explain_tradeoffs(self, strategy):
        explanation = f"Chose {strategy['model_family']} due to: {strategy['reason']}."
        if strategy.get("risks"):
            explanation += f" Risks detected: {', '.join(strategy['risks'])}."
        explanation += f" Confidence score: {strategy.get('confidence')}."
        return explanation