/**
 * Section 6: Predictive Modeling & Advanced Analytics Guidance
 * Type definitions for modeling recommendations and analysis
 */
export type ModelingTaskType = 'regression' | 'binary_classification' | 'multiclass_classification' | 'clustering' | 'time_series_forecasting' | 'anomaly_detection' | 'survival_analysis' | 'dimensionality_reduction' | 'association_rule_mining' | 'density_estimation' | 'manifold_learning' | 'topic_modeling' | 'synthetic_target_generation';
export type AlgorithmCategory = 'linear_models' | 'tree_based' | 'ensemble_methods' | 'neural_networks' | 'probabilistic_models' | 'instance_based' | 'unsupervised';
export type ModelComplexity = 'simple' | 'moderate' | 'complex' | 'advanced';
export type InterpretabilityLevel = 'high' | 'medium' | 'low' | 'black_box';
export type ConfidenceLevel = 'very_high' | 'high' | 'medium' | 'low';
export type RiskLevel = 'low' | 'medium' | 'high' | 'critical';
export interface ModelingTask {
    taskType: ModelingTaskType;
    targetVariable?: string;
    targetType: 'continuous' | 'binary' | 'multiclass' | 'ordinal' | 'none';
    inputFeatures: string[];
    businessObjective: string;
    technicalObjective: string;
    justification: string[];
    dataRequirements: DataRequirement[];
    feasibilityScore: number;
    confidenceLevel: ConfidenceLevel;
    estimatedComplexity: ModelComplexity;
    potentialChallenges: string[];
    successMetrics: string[];
}
export interface DataRequirement {
    requirement: string;
    currentStatus: 'met' | 'partially_met' | 'not_met';
    importance: 'critical' | 'important' | 'optional';
    mitigation?: string;
}
export interface AlgorithmRecommendation {
    algorithmName: string;
    category: AlgorithmCategory;
    suitabilityScore: number;
    complexity: ModelComplexity;
    interpretability: InterpretabilityLevel;
    strengths: string[];
    weaknesses: string[];
    dataRequirements: string[];
    hyperparameters: HyperparameterGuide[];
    implementationFrameworks: string[];
    evaluationMetrics: string[];
    reasoningNotes: string[];
}
export interface HyperparameterGuide {
    parameterName: string;
    description: string;
    defaultValue: any;
    recommendedRange: string;
    tuningStrategy: string;
    importance: 'critical' | 'important' | 'optional';
}
export interface CARTAnalysis {
    methodology: string;
    splittingCriterion: 'gini' | 'entropy' | 'variance_reduction';
    stoppingCriteria: StoppingCriterion[];
    pruningStrategy: PruningStrategy;
    treeInterpretation: TreeInterpretation;
    residualAnalysis?: ResidualAnalysis;
    featureImportance: FeatureImportance[];
    visualizationRecommendations: string[];
}
export interface StoppingCriterion {
    criterion: string;
    recommendedValue: any;
    reasoning: string;
}
export interface PruningStrategy {
    method: 'cost_complexity' | 'reduced_error' | 'minimum_error';
    crossValidationFolds: number;
    complexityParameter: number;
    reasoning: string;
}
export interface TreeInterpretation {
    treeDepth: number;
    numberOfLeaves: number;
    keyDecisionPaths: DecisionPath[];
    businessRules: string[];
    visualizationGuidance: string;
}
export interface DecisionPath {
    pathDescription: string;
    conditions: string[];
    prediction: any;
    supportingInstances: number;
    businessMeaning: string;
}
export interface ResidualAnalysis {
    residualDiagnostics: ResidualDiagnostic[];
    normalityTests: NormalityTest[];
    heteroscedasticityTests: HeteroscedasticityTest[];
    autocorrelationTests: AutocorrelationTest[];
    outlierAnalysis: OutlierAnalysis;
    modelAssumptions: ModelAssumption[];
    improvementSuggestions: string[];
}
export interface ResidualDiagnostic {
    plotType: 'residuals_vs_fitted' | 'qq_plot' | 'histogram' | 'scale_location';
    description: string;
    idealPattern: string;
    observedPattern: string;
    interpretation: string;
    actionRequired: boolean;
    recommendations: string[];
}
export interface NormalityTest {
    testName: 'shapiro_wilk' | 'jarque_bera' | 'kolmogorov_smirnov';
    statistic: number;
    pValue: number;
    interpretation: string;
    conclusion: string;
}
export interface HeteroscedasticityTest {
    testName: 'breusch_pagan' | 'white_test' | 'goldfeld_quandt';
    statistic: number;
    pValue: number;
    interpretation: string;
    conclusion: string;
}
export interface AutocorrelationTest {
    testName: 'durbin_watson' | 'ljung_box';
    statistic: number;
    pValue?: number;
    interpretation: string;
    conclusion: string;
}
export interface OutlierAnalysis {
    outlierIndices: number[];
    outlierTypes: OutlierType[];
    influentialPoints: InfluentialPoint[];
    recommendations: string[];
}
export interface OutlierType {
    index: number;
    type: 'leverage' | 'residual' | 'influential';
    severity: 'mild' | 'moderate' | 'severe';
    description: string;
}
export interface InfluentialPoint {
    index: number;
    cooksDistance: number;
    leverage: number;
    studentizedResidual: number;
    impact: string;
}
export interface ModelAssumption {
    assumption: string;
    status: 'satisfied' | 'violated' | 'questionable';
    evidence: string;
    impact: string;
    remediation: string[];
}
export interface ModelingWorkflow {
    workflowSteps: WorkflowStep[];
    bestPractices: BestPractice[];
    dataSplittingStrategy: DataSplittingStrategy;
    crossValidationApproach: CrossValidationApproach;
    hyperparameterTuning: HyperparameterTuningStrategy;
    evaluationFramework: EvaluationFramework;
    interpretationGuidance: InterpretationGuidance;
}
export interface WorkflowStep {
    stepNumber: number;
    stepName: string;
    description: string;
    inputs: string[];
    outputs: string[];
    estimatedTime: string;
    difficulty: 'beginner' | 'intermediate' | 'advanced';
    tools: string[];
    considerations: string[];
    commonPitfalls: string[];
}
export interface BestPractice {
    category: string;
    practice: string;
    reasoning: string;
    implementation: string;
    relatedSteps: number[];
}
export interface DataSplittingStrategy {
    strategy: 'random' | 'stratified' | 'temporal' | 'group_based';
    trainPercent: number;
    validationPercent: number;
    testPercent: number;
    reasoning: string;
    implementation: string;
    considerations: string[];
}
export interface CrossValidationApproach {
    method: 'k_fold' | 'stratified_k_fold' | 'time_series_split' | 'leave_one_out';
    folds: number;
    reasoning: string;
    implementation: string;
    expectedBenefit: string;
}
export interface HyperparameterTuningStrategy {
    method: 'grid_search' | 'random_search' | 'bayesian_optimization' | 'genetic_algorithm';
    searchSpace: SearchSpace[];
    optimizationMetric: string;
    budgetConstraints: BudgetConstraint[];
    earlyStoppingCriteria?: string;
}
export interface SearchSpace {
    parameterName: string;
    parameterType: 'continuous' | 'discrete' | 'categorical';
    searchRange: any;
    searchDistribution?: string;
    priority: 'high' | 'medium' | 'low';
}
export interface BudgetConstraint {
    constraintType: 'time' | 'computational' | 'cost';
    limit: string;
    reasoning: string;
}
export interface EvaluationFramework {
    primaryMetrics: EvaluationMetric[];
    secondaryMetrics: EvaluationMetric[];
    interpretationGuidelines: MetricInterpretation[];
    benchmarkComparisons: BenchmarkComparison[];
    businessImpactAssessment: BusinessImpactMetric[];
    robustnessTests: RobustnessTest[];
}
export interface EvaluationMetric {
    metricName: string;
    metricType: 'accuracy' | 'precision' | 'recall' | 'f1' | 'auc' | 'rmse' | 'mae' | 'r2';
    description: string;
    interpretation: string;
    idealValue: number | string;
    acceptableRange: string;
    calculationMethod: string;
    useCases: string[];
    limitations: string[];
}
export interface MetricInterpretation {
    metricName: string;
    valueRanges: ValueRange[];
    contextualFactors: string[];
    comparisonGuidelines: string[];
}
export interface ValueRange {
    range: string;
    interpretation: string;
    actionRecommendation: string;
}
export interface BenchmarkComparison {
    benchmarkType: 'baseline' | 'naive' | 'domain_standard' | 'state_of_art';
    description: string;
    expectedPerformance: string;
    comparisonMethod: string;
}
export interface BusinessImpactMetric {
    metricName: string;
    businessValue: string;
    measurementMethod: string;
    timeframe: string;
    dependencies: string[];
}
export interface RobustnessTest {
    testName: string;
    testType: 'data_drift' | 'adversarial' | 'cross_validation' | 'sensitivity';
    description: string;
    implementation: string;
    passingCriteria: string;
}
export interface InterpretationGuidance {
    globalInterpretation: GlobalInterpretation;
    localInterpretation: LocalInterpretation;
    featureImportance: FeatureImportanceAnalysis;
    modelBehaviorAnalysis: ModelBehaviorAnalysis;
    visualizationStrategies: VisualizationStrategy[];
}
export interface GlobalInterpretation {
    methods: string[];
    overallModelBehavior: string;
    keyPatterns: string[];
    featureRelationships: string[];
    modelLimitations: string[];
}
export interface LocalInterpretation {
    methods: string[];
    exampleExplanations: ExampleExplanation[];
    explanationReliability: string;
    useCases: string[];
}
export interface ExampleExplanation {
    instanceId: string;
    prediction: any;
    featureContributions: FeatureContribution[];
    confidence: number;
    explanation: string;
}
export interface FeatureContribution {
    featureName: string;
    contribution: number;
    direction: 'positive' | 'negative';
    importance: number;
    explanation: string;
}
export interface FeatureImportanceAnalysis {
    importanceMethod: 'permutation' | 'gini' | 'information_gain' | 'shap';
    featureRankings: FeatureImportance[];
    stabilityAnalysis: string;
    businessRelevance: string[];
}
export interface FeatureImportance {
    featureName: string;
    importance: number;
    rank: number;
    confidenceInterval?: [number, number];
    businessMeaning: string;
}
export interface ModelBehaviorAnalysis {
    decisionBoundaries: string;
    nonlinearEffects: string[];
    interactionEffects: InteractionEffect[];
    predictionConfidence: string;
}
export interface InteractionEffect {
    features: [string, string];
    effectType: 'synergistic' | 'antagonistic' | 'conditional';
    magnitude: number;
    description: string;
    businessImplication: string;
}
export interface VisualizationStrategy {
    visualizationType: string;
    purpose: string;
    implementation: string;
    interpretationGuide: string;
    toolSuggestions: string[];
}
export interface EthicsAnalysis {
    biasAssessment: BiasAssessment;
    fairnessMetrics: FairnessMetric[];
    ethicalConsiderations: EthicalConsideration[];
    transparencyRequirements: TransparencyRequirement[];
    governanceRecommendations: GovernanceRecommendation[];
    riskMitigation: RiskMitigation[];
}
export interface BiasAssessment {
    potentialBiasSources: BiasSource[];
    sensitiveAttributes: SensitiveAttribute[];
    biasTests: BiasTest[];
    overallRiskLevel: RiskLevel;
    mitigationStrategies: string[];
}
export interface BiasSource {
    sourceType: 'historical' | 'selection' | 'measurement' | 'algorithmic';
    description: string;
    riskLevel: RiskLevel;
    evidence: string[];
    mitigation: string[];
}
export interface SensitiveAttribute {
    attributeName: string;
    attributeType: 'protected_class' | 'proxy_variable' | 'derived';
    availableInData: boolean;
    riskAssessment: string;
    handlingRecommendation: string;
}
export interface BiasTest {
    testName: string;
    testType: 'statistical_parity' | 'equalized_odds' | 'demographic_parity';
    result: number;
    interpretation: string;
    passingThreshold: number;
    recommendations: string[];
}
export interface FairnessMetric {
    metricName: string;
    value: number;
    interpretation: string;
    acceptableRange: string;
    improvementSuggestions: string[];
}
export interface EthicalConsideration {
    consideration: string;
    domain: 'privacy' | 'consent' | 'transparency' | 'accountability' | 'fairness';
    riskLevel: RiskLevel;
    requirements: string[];
    implementation: string[];
}
export interface TransparencyRequirement {
    requirement: string;
    level: 'model_level' | 'prediction_level' | 'system_level';
    implementation: string;
    audience: string[];
    complianceNeed: boolean;
}
export interface GovernanceRecommendation {
    area: string;
    recommendation: string;
    priority: 'immediate' | 'short_term' | 'long_term';
    implementation: string;
    stakeholders: string[];
}
export interface RiskMitigation {
    riskType: string;
    mitigationStrategy: string;
    implementation: string;
    monitoring: string;
    effectiveness: string;
}
export interface Section6Config {
    focusAreas: ModelingTaskType[];
    complexityPreference: ModelComplexity;
    interpretabilityRequirement: InterpretabilityLevel;
    ethicsLevel: 'basic' | 'standard' | 'comprehensive';
    includeAdvancedMethods: boolean;
    customDomainRules?: string[];
    performanceThresholds: Record<string, number>;
    businessContext?: string;
    enableClusteringRecommendations?: boolean;
    enableCARTAnalysis?: boolean;
    maxRecordsForAnalysis?: number;
}
export interface Section6Progress {
    stage: 'initialization' | 'task_identification' | 'algorithm_selection' | 'workflow_design' | 'evaluation_framework' | 'ethics_analysis' | 'interpretation_guide' | 'finalization';
    percentage: number;
    message: string;
    currentStep: number;
    totalSteps: number;
    estimatedTimeRemaining?: string;
}
export interface Section6Warning {
    category: 'data_quality' | 'modeling' | 'ethics' | 'interpretation' | 'implementation';
    severity: 'low' | 'medium' | 'high' | 'critical';
    message: string;
    impact: string;
    suggestion: string;
    affectedComponents: string[];
}
export interface Section6Result {
    modelingAnalysis: ModelingAnalysis;
    warnings: Section6Warning[];
    performanceMetrics: Section6PerformanceMetrics;
    metadata: Section6Metadata;
}
export interface ModelingAnalysis {
    identifiedTasks: ModelingTask[];
    algorithmRecommendations: AlgorithmRecommendation[];
    cartAnalysis?: CARTAnalysis;
    residualAnalysis?: ResidualAnalysis;
    workflowGuidance: ModelingWorkflow;
    evaluationFramework: EvaluationFramework;
    interpretationGuidance: InterpretationGuidance;
    ethicsAnalysis: EthicsAnalysis;
    implementationRoadmap: ImplementationRoadmap;
    unsupervisedAnalysis?: UnsupervisedAnalysisResult;
}
export interface ImplementationRoadmap {
    phases: ImplementationPhase[];
    estimatedTimeline: string;
    resourceRequirements: ResourceRequirement[];
    riskFactors: string[];
    successCriteria: string[];
}
export interface ImplementationPhase {
    phaseNumber: number;
    phaseName: string;
    duration: string;
    deliverables: string[];
    dependencies: string[];
    riskLevel: RiskLevel;
}
export interface ResourceRequirement {
    resourceType: 'computational' | 'human' | 'data' | 'infrastructure';
    requirement: string;
    criticality: 'essential' | 'important' | 'optional';
    alternatives: string[];
}
export interface Section6PerformanceMetrics {
    analysisTimeMs: number;
    tasksIdentified: number;
    algorithmsEvaluated: number;
    ethicsChecksPerformed: number;
    recommendationsGenerated: number;
    recordsAnalyzed?: number;
}
export interface Section6Metadata {
    analysisApproach: string;
    complexityLevel: ModelComplexity;
    recommendationConfidence: ConfidenceLevel;
    primaryFocus: string[];
    limitationsIdentified: string[];
}
export interface SyntheticTargetRecommendation {
    targetName: string;
    targetType: 'clustering_based' | 'outlier_based' | 'composite' | 'temporal' | 'domain_derived';
    description: string;
    businessValue: string;
    technicalImplementation: string;
    sourceColumns: string[];
    expectedCardinality?: number;
    feasibilityScore: number;
    codeExample: string;
    validationStrategy: string;
    useCases: string[];
}
export interface UnsupervisedLearningRecommendation {
    approach: 'clustering' | 'dimensionality_reduction' | 'association_mining' | 'anomaly_detection' | 'density_estimation';
    algorithmName: string;
    description: string;
    businessValue: string;
    technicalDetails: UnsupervisedTechnicalDetails;
    codeImplementation: CodeImplementation;
    evaluationMetrics: string[];
    interpretationGuidance: string[];
    scalabilityNotes: string[];
}
export interface UnsupervisedTechnicalDetails {
    inputFeatures: string[];
    preprocessing: string[];
    hyperparameters: HyperparameterGuide[];
    computationalComplexity: string;
    memoryRequirements: string;
    optimalDataSize: string;
}
export interface CodeImplementation {
    framework: 'scikit-learn' | 'pandas' | 'numpy' | 'tensorflow' | 'pytorch';
    importStatements: string[];
    preprocessingCode: string[];
    mainImplementation: string[];
    evaluationCode: string[];
    visualizationCode?: string[];
}
export interface AutoMLRecommendation {
    platform: 'H2O_AutoML' | 'AutoGluon' | 'MLflow' | 'DataRobot' | 'Google_AutoML' | 'Azure_AutoML';
    suitabilityScore: number;
    strengths: string[];
    limitations: string[];
    dataRequirements: string[];
    estimatedCost: string;
    setupComplexity: ModelComplexity;
    codeExample: string;
    configurationRecommendations: Record<string, any>;
}
export interface FeatureEngineeringRecipe {
    recipeName: string;
    description: string;
    applicableColumns: string[];
    businessRationale: string;
    codeImplementation: string[];
    expectedImpact: string;
    prerequisites: string[];
    riskFactors: string[];
}
export interface UnsupervisedAnalysisResult {
    syntheticTargets: SyntheticTargetRecommendation[];
    unsupervisedApproaches: UnsupervisedLearningRecommendation[];
    autoMLRecommendations: AutoMLRecommendation[];
    featureEngineeringRecipes: FeatureEngineeringRecipe[];
    deploymentConsiderations: DeploymentConsideration[];
}
export interface DeploymentConsideration {
    aspect: 'data_pipeline' | 'monitoring' | 'api_schema' | 'infrastructure' | 'maintenance';
    requirements: string[];
    recommendations: string[];
    riskFactors: string[];
    codeTemplates?: string[];
}
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