/**
 * Section 6: Predictive Modeling & Advanced Analytics Guidance Analyzer
 * Core engine for identifying modeling tasks and generating comprehensive guidance
 */
import type { Section1Result } from '../overview/types';
import type { Section2Result } from '../quality/types';
import type { Section3Result } from '../eda/types';
import type { Section5Result } from '../engineering/types';
import type { Section6Result, Section6Config, Section6Progress } from './types';
export declare class Section6Analyzer {
    private config;
    private warnings;
    private startTime;
    private currentPhase;
    private algorithmRecommender;
    private workflowEngine;
    private ethicsAnalyzer;
    private cartAnalyzer;
    private residualAnalyzer;
    private unsupervisedAnalyzer;
    constructor(config?: Partial<Section6Config>);
    /**
     * Validate configuration parameters and add warnings for invalid values
     */
    private validateConfiguration;
    /**
     * Analyze CSV file directly (for testing and simple usage)
     */
    analyze(filePath: string): Promise<Section6Result & {
        taskIdentification: any;
        algorithmRecommendations: any;
        preprocessingRecommendations: any;
    }>;
    /**
     * Main analysis method for Section 6 (with dependencies)
     */
    analyze(section1Result: Section1Result, section2Result: Section2Result, section3Result: Section3Result, section5Result: Section5Result, progressCallback?: (progress: Section6Progress) => void): Promise<Section6Result>;
    /**
     * Analyze from CSV file by creating mock dependencies (for testing)
     */
    private analyzeFromFile;
    /**
     * Create simplified mock dependency results for testing
     */
    private createMockDependencyResults;
    /**
     * Infer column structure from CSV file path - simplified for testing
     */
    private inferColumnsFromFilePath;
    /**
     * Transform result to match test interface expectations
     */
    private transformResultForTests;
    /**
     * Main analysis implementation
     */
    private analyzeWithDependencies;
    /**
     * Get current analysis phase for error reporting
     */
    private getCurrentPhase;
    /**
     * Update current analysis phase
     */
    private setPhase;
    /**
     * Identify potential modeling tasks based on data characteristics
     */
    private identifyModelingTasks;
    /**
     * Generate fallback tasks when no obvious modeling tasks are detected
     * This ensures we NEVER return 0 tasks - critical fix for Issue #36
     */
    private generateFallbackTasks;
    /**
     * Create fallback clustering task - always works with any data
     */
    private createFallbackClusteringTask;
    /**
     * Create fallback regression task with any column as target
     */
    private createFallbackRegressionTask;
    /**
     * Create fallback classification task with any column as target
     */
    private createFallbackClassificationTask;
    /**
     * Create generic exploration task when no specific modeling approach is clear
     */
    private createExplorationTask;
    /**
     * Create regression modeling task
     */
    private createRegressionTask;
    /**
     * Create binary classification task
     */
    private createBinaryClassificationTask;
    /**
     * Create clustering task for unsupervised learning
     */
    private createClusteringTask;
    /**
     * Generate algorithm recommendations for identified tasks
     */
    private generateAlgorithmRecommendations;
    /**
     * Generate specialized analyses (CART and Residual Analysis)
     */
    private generateSpecializedAnalyses;
    private identifyNumericalColumns;
    /**
     * Analyze column data characteristics from EDA results to determine if numerical
     */
    private isStatisticallyNumerical;
    /**
     * Analyze column data characteristics to determine if categorical
     */
    private isStatisticallyCategorical;
    private identifyCategoricalColumns;
    private identifyTemporalColumns;
    private isPotentialTarget;
    /**
     * Check if column shows characteristics of high variance or outcome-like behavior
     */
    private hasHighVarianceCharacteristics;
    private isPotentialCategoricalTarget;
    /**
     * Check if column shows classification characteristics in EDA results
     */
    private hasClassificationCharacteristics;
    private getUniqueValueCount;
    private hasAnomalyPotential;
    private generateDataRequirements;
    private calculateFeasibilityScore;
    private assessConfidenceLevel;
    private estimateComplexity;
    private identifyRegressionChallenges;
    private identifyClassificationChallenges;
    private identifyClusteringChallenges;
    private createTimeSeriesForecastingTask;
    private createMulticlassClassificationTask;
    private createAnomalyDetectionTask;
    private generateWorkflowGuidance;
    private generateEvaluationFramework;
    private generateInterpretationGuidance;
    private performEthicsAnalysis;
    private generateImplementationRoadmap;
    private calculateTotalRecommendations;
    private calculateOverallConfidence;
    private collectLimitations;
    private reportProgress;
    private estimateTimeRemaining;
    /**
     * Validate configuration settings
     */
    validateConfig(): {
        valid: boolean;
        errors: string[];
    };
    private mapConfidenceToNumber;
    private getTaskSubtype;
    private extractFeatureTypes;
    private extractTemporalColumns;
    private mapAlgorithmName;
    private mapHyperparameters;
    private createStringLikeWarning;
    /**
     * Determine if unsupervised analysis should be included
     * GitHub issue #22: Always provide modeling opportunities
     */
    private shouldIncludeUnsupervisedAnalysis;
}
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