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Project Deep-Dive and Feature Selection
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Project Deep-Dive and Feature Selection

EasySQL · PostgreSQL

Problem

Mostly asked questions about projects in my resume and digged deeper on why I did what I did in the project, and asked you to identify important features for a case study solution.

Use feature_catalog and feature_evaluations to identify important features. Include active features with missing rates at or below 0.30 and average importance scores of at least 0.60, then retain the three highest-scoring features.

Output

  1. One row per selected feature with feature_name, feature_type, avg_importance, evaluation_count, and importance_rank.
  2. Sort by importance_rank ascending, then feature_id ascending for ties.

Schema

feature_catalog
ColumnTypeDescription
feature_idPKINTUnique feature identifier
feature_nameVARCHAR(100)Feature name
feature_typeVARCHAR(30)Feature data type classification
missing_rateDECIMAL(4,3)Fraction of feature values that are missing
is_activeBOOLEANWhether the feature is currently eligible for use
feature_evaluations
ColumnTypeDescription
evaluation_idPKINTUnique evaluation identifier
feature_idINTReferenced feature identifier
importance_scoreDECIMAL(4,3)Importance score assigned during an evaluation
evaluator_nameVARCHAR(100)Name of the evaluator
Tablesfeature_catalogfeature_evaluations
Interviewer

Your question is Project Deep-Dive and Feature Selection. Start with the requirements and the two tables in the Question tab.

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