Module: config.py

Configuration Settings

The config.py module contains configuration settings for the clustering process. These settings include model type, number of clusters, random state, and feature columns.

Configuration Variables

• MODEL_TYPE: Specifies the type of clustering model to be used. Options could include "KMeans", "DBSCAN", "AgglomerativeClustering", etc.

  • Example: "KMeans"

• N_CLUSTERS: The default number of clusters to be formed.

  • Example: 3

• RANDOM_STATE: Controls the randomness of the clustering process for reproducibility.

  • Example: 42

• FEATURE_COLUMNS: A list of column names to be used as features in the model. These columns are used for clustering.

  • Example:

    [
        "sepal_length",
        "sepal_width",
        "petal_length",
        "petal_width"
    ]

Example Configuration for Iris Dataset

The provided configuration is set up for clustering the Iris dataset:

• MODEL_TYPE: "KMeans"
• N_CLUSTERS: 3
• RANDOM_STATE: 42
• FEATURE_COLUMNS: List of feature columns relevant to the Iris dataset:

  [
      "sepal_length",
      "sepal_width",
      "petal_length",
      "petal_width"
  ]