datapilot-cli
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Enterprise-grade streaming multi-format data analysis with comprehensive statistical insights and intelligent relationship detection - supports CSV, JSON, Excel, TSV, Parquet - memory-efficient, cross-platform
128 lines • 4.37 kB
TypeScript
/**
* 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 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;
/**
* Identify potential modeling tasks based on data characteristics
*/
private identifyModelingTasks;
/**
* 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;
private identifyCategoricalColumns;
private identifyTemporalColumns;
private isPotentialTarget;
private isPotentialCategoricalTarget;
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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