/**
 * Intelligent Algorithm Selection Analyzer
 * Advanced algorithm selection engine that provides sophisticated, dataset-aware ML recommendations
 *
 * Risk-averse implementation strategy:
 * - Incremental analysis with comprehensive fallbacks
 * - Multi-criteria decision framework with uncertainty handling
 * - Progressive enhancement of recommendation sophistication
 * - Backward compatibility with existing systems
 */
import type { Section1Result } from '../../overview/types';
import type { Section2Result } from '../../quality/types';
import type { Section3Result } from '../../eda/types';
import type { DatasetComplexityProfile } from '../advanced-characterization/types';
import type { AlgorithmSelectionProfile, AlgorithmSelectionConfig, SelectionProgress } from './types';
/**
 * Main analyzer class for intelligent algorithm selection
 */
export declare class IntelligentAlgorithmSelectionAnalyzer {
    private config;
    private warnings;
    private startTime;
    private progress;
    constructor(config?: Partial<AlgorithmSelectionConfig>);
    /**
     * Main analysis method - performs comprehensive algorithm selection
     */
    analyze(section1Result: Section1Result, section2Result: Section2Result, section3Result: Section3Result, complexityProfile: DatasetComplexityProfile, progressCallback?: (progress: SelectionProgress) => void): Promise<AlgorithmSelectionProfile>;
    /**
     * Performs incremental algorithm selection with comprehensive error handling
     */
    private performIncrementalSelection;
    /**
     * Generate candidate algorithms based on dataset characteristics and task requirements
     */
    private generateCandidateAlgorithms;
    /**
     * Perform multi-criteria evaluation of candidate algorithms
     */
    private performMultiCriteriaEvaluation;
    /**
     * Generate performance predictions for selected algorithms
     */
    private generatePerformancePredictions;
    /**
     * Initialize configuration with defaults
     */
    private initializeConfig;
    /**
     * Initialize progress tracking
     */
    private initializeProgress;
    /**
     * Reset analysis state for new analysis
     */
    private resetAnalysisState;
    /**
     * Update progress and notify callback
     */
    private updateProgress;
    /**
     * Estimate remaining time based on progress
     */
    private estimateTimeRemaining;
    /**
     * Calculate total analysis steps
     */
    private calculateTotalSteps;
    /**
     * Validate inputs before analysis
     */
    private validateInputs;
    /**
     * Extract decision context from all input sources
     */
    private extractDecisionContext;
    /**
     * Add warning to collection
     */
    private addWarning;
    /**
     * Handle analysis errors with proper categorization
     */
    private handleAnalysisError;
    /**
     * Generate selection metadata
     */
    private generateSelectionMetadata;
    private inferTaskType;
    private generateClassificationCandidates;
    private generateRegressionCandidates;
    private generateClusteringCandidates;
    private generateTimeSeriesCandidates;
    private generateAnomalyDetectionCandidates;
    private generateGeneralCandidates;
    private filterCandidatesByConstraints;
    private getFallbackCandidates;
    private evaluateCandidate;
    private performBasicEvaluation;
    private predictAlgorithmPerformance;
    private generateTheoreticalPredictions;
    private performRiskAssessment;
    private generateEnsembleRecommendations;
    private generateHyperparameterGuidance;
    private developImplementationStrategy;
    private generateSelectionReasoning;
    private assessDataQuality;
}
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