From 74fc670324ea4f568cbd8eb2fbb6868ea542aff7 Mon Sep 17 00:00:00 2001 From: Pratik Date: Sun, 29 Dec 2024 13:47:15 -0500 Subject: [PATCH 1/3] Dunn Index Added a new section for Dunn Index (Clustering) metric --- book/4-clustering.tex | 71 ++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 70 insertions(+), 1 deletion(-) diff --git a/book/4-clustering.tex b/book/4-clustering.tex index 38b70f6..77211fb 100644 --- a/book/4-clustering.tex +++ b/book/4-clustering.tex @@ -137,4 +137,73 @@ \subsection{Silhouette Score} \clearpage \thispagestyle{clusteringstyle} \section{ Consensus Score} -\subsection{ Consensus Score} \ No newline at end of file +\subsection{ Consensus Score} + + +% ---------- Dunn Index ---------- +\clearpage +\thispagestyle{clusteringstyle} +\section{ Dunn Index} + +% Define colors +\definecolor{nmlpurple}{RGB}{128,0,128} + +The Dunn Index is used to evaluate the quality of clusters by measuring both the separation between the clusters and compactness within clusters. It considers the smallest distance between points in different clusters (inter-cluster distance) and the largest distance within a single cluster (intra-cluster distance) to evaluate how well-defined the clusters are. A higher Dunn Index indicates that the clustering configuration has well-separated and compact clusters, while a lower Dunn Index suggests poor separation or high dispersion within clusters.\\ + +The Dunn Index for a given clustering solution with \( k \) clusters \( C_1, C_2, \ldots, C_k \) is defined as: + +\begin{center} + \begin{tikzpicture} + \node[inner sep=2pt, font=\Large] (a) { + $\displaystyle + D = \frac{\min\limits_{1 \leq i < j \leq k} \{ \text{dist}(C_i, C_j) \}}{\max\limits_{1 \leq i \leq k} \{ \text{diam}(C_i) \}} + $ + }; + \draw[-latex, cyan, semithick] ($(a.north east)+(0.2,-0.1)$) to[bend left=15] node[pos=1, right] {measures inter-cluster distance} +(2,0.5); + \draw[-latex, nmlpurple, semithick] ($(a.south east)+(0.2,0.1)$) to[bend right=15] node[pos=1, right] {measures intra-cluster distance} +(2,-0.5); + \end{tikzpicture} +\end{center} + +where: +\begin{itemize} + \item \(\text{dist}(C_i, C_j)\) represents the distance between clusters \( C_i \) and \( C_j \), often calculated as the minimum distance between any two points in different clusters (inter-cluster distance). + \item \(\text{diam}(C_i)\) represents the diameter of cluster \( C_i \), typically defined as the maximum distance between any two points within the same cluster (intra-cluster distance). +\end{itemize} + +\textit{The Dunn Index ranges from 0 to infinity, with higher values indicating better-defined clusters. Values closer to 0 suggest that clusters are either overlapping or not sufficiently compact.}\\ + +\textbf{When to Use Dunn Index?} + +The Dunn Index is primarily used when evaluating clustering results in applications where the structure and separation of clusters are critical. It is useful in determining whether a clustering algorithm has successfully created distinct, dense clusters without overlap. The Dunn Index is particularly valuable for comparing clustering algorithms, such as K-means, hierarchical clustering, and DBSCAN, especially when the number of clusters is uncertain, or various configurations need to be tested. + +% strength and weakness box +\coloredboxes{ + \item Considers both intra-cluster compactness and inter-cluster separation. + \item Useful for determining the best number of clusters. + \item Higher values indicate better-defined clusters. + \item Helps compare clustering algorithms. +} +{ + \item Outliers can reduce the Dunn Index value, affecting accuracy. + \item High resource use for large datasets. + \item Less effective for irregular shapes. + \item Sensitive to unnormalized features. + \item Can be unreliable in high-dimensional spaces. +} + +% Inserting the image +\begin{figure}[h!] + \centering + \includegraphics[width=\textwidth]{/figures/Dunn_Index_Visualized.png} + \caption{Illustration of High and Low Dunn Index Values} +\end{figure} + +% Adding the explanation below the image +\textbf{In the visualization above:} +\begin{itemize} + \item \textbf{Left Plot (High Dunn Index):} This example illustrates clusters that are well-separated and compact. Each cluster (shown in blue, green, and purple) is distinct, with clear boundaries and minimal overlap with other clusters. The points within each cluster are closely packed, which leads to a small maximum intra-cluster distance (diameter). Furthermore, the minimum distance between clusters (inter-cluster distance) is large, reinforcing the separation between clusters. These characteristics yield a high Dunn Index, signifying a high-quality clustering configuration where clusters are well-defined and do not overlap. + \item \textbf{Right Plot (Low Dunn Index):} This example illustrates clusters that are overlapping and dispersed. The clusters lack distinct boundaries, and points from different clusters are intermixed. The large maximum intra-cluster distance, due to dispersed points within clusters, combined with a small minimum inter-cluster distance, because of overlapping clusters, results in a low Dunn Index. This clustering configuration suggests poor clustering quality, as the clusters are not compact or well-separated. +\end{itemize} + +\subsection{ Dunn Index} + From 2beb21d7c36a79e0a60bae64635ad3775003ee98 Mon Sep 17 00:00:00 2001 From: Pratik Watwani Date: Fri, 7 Feb 2025 11:42:33 -0500 Subject: [PATCH 2/3] added clustering plots jupyter notebook --- notebooks/clustering_plots.ipynb | 143 +++++++++++++++++++++++++++++++ 1 file changed, 143 insertions(+) create mode 100644 notebooks/clustering_plots.ipynb diff --git a/notebooks/clustering_plots.ipynb b/notebooks/clustering_plots.ipynb new file mode 100644 index 0000000..47d0069 --- /dev/null +++ b/notebooks/clustering_plots.ipynb @@ -0,0 +1,143 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn.datasets import make_blobs\n", + "from sklearn.cluster import KMeans\n", + "from scipy.spatial.distance import cdist" + ], + "metadata": { + "id": "-pHq9OsKR6Dr" + }, + "execution_count": 2, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "**Dunn Index**" + ], + "metadata": { + "id": "Mhj_ScRSR8rm" + } + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 507 + }, + "id": "V8x_cvnoRdqX", + "outputId": "ef4622c4-1ff2-442a-c8b5-562e4c3e22ce" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "# Function to compute Dunn Index\n", + "def dunn_index(X, labels):\n", + " unique_clusters = np.unique(labels)\n", + "\n", + " # Compute intra-cluster distances (cluster diameters)\n", + " intra_distances = []\n", + " for cluster in unique_clusters:\n", + " cluster_points = X[labels == cluster]\n", + " if len(cluster_points) > 1:\n", + " max_intra_dist = np.max(cdist(cluster_points, cluster_points))\n", + " intra_distances.append(max_intra_dist)\n", + "\n", + " max_diameter = max(intra_distances)\n", + "\n", + " # Compute inter-cluster distances (minimum between-cluster distances)\n", + " inter_distances = []\n", + " for i in range(len(unique_clusters)):\n", + " for j in range(i + 1, len(unique_clusters)):\n", + " cluster_i = X[labels == unique_clusters[i]]\n", + " cluster_j = X[labels == unique_clusters[j]]\n", + " min_inter_dist = np.min(cdist(cluster_i, cluster_j))\n", + " inter_distances.append(min_inter_dist)\n", + "\n", + " min_inter_cluster_distance = min(inter_distances)\n", + "\n", + " # Compute Dunn Index\n", + " return min_inter_cluster_distance / max_diameter\n", + "\n", + "# Set style\n", + "sns.set_style(\"whitegrid\")\n", + "\n", + "# Create figure with two subplots\n", + "fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n", + "\n", + "# -------- High Dunn Index (Well-Separated Clusters) --------\n", + "X_high, y_high = make_blobs(n_samples=150, centers=3, cluster_std=0.5, random_state=42)\n", + "\n", + "# Apply K-Means clustering\n", + "kmeans_high = KMeans(n_clusters=3, random_state=42, n_init=10)\n", + "labels_high = kmeans_high.fit_predict(X_high)\n", + "\n", + "# Compute Dunn Index\n", + "dunn_high = dunn_index(X_high, labels_high)\n", + "\n", + "# Plot High Dunn Index\n", + "axes[0].scatter(X_high[:, 0], X_high[:, 1], c=labels_high, cmap=\"viridis\", edgecolor=\"black\", alpha=0.8)\n", + "axes[0].set_title(f\"High Dunn Index (Well-Separated Clusters)\\nDunn Index = {dunn_high:.2f}\")\n", + "axes[0].set_xticks([])\n", + "axes[0].set_yticks([])\n", + "\n", + "# -------- Low Dunn Index (Overlapping Clusters) --------\n", + "np.random.seed(42)\n", + "X_low = np.vstack([\n", + " np.random.randn(50, 2) * 0.8 + np.array([0, 0]),\n", + " np.random.randn(50, 2) * 0.8 + np.array([1, 1]),\n", + " np.random.randn(50, 2) * 0.8 + np.array([2, 2]),\n", + "])\n", + "y_low_true = np.array([0] * 50 + [1] * 50 + [2] * 50)\n", + "\n", + "# Apply K-Means clustering\n", + "kmeans_low = KMeans(n_clusters=3, random_state=42, n_init=10)\n", + "labels_low = kmeans_low.fit_predict(X_low)\n", + "\n", + "# Compute Dunn Index\n", + "dunn_low = dunn_index(X_low, labels_low)\n", + "\n", + "# Plot Low Dunn Index\n", + "axes[1].scatter(X_low[:, 0], X_low[:, 1], c=labels_low, cmap=\"viridis\", edgecolor=\"black\", alpha=0.8)\n", + "axes[1].set_title(f\"Low Dunn Index (Overlapping Clusters)\\nDunn Index = {dunn_low:.2f}\")\n", + "axes[1].set_xticks([])\n", + "axes[1].set_yticks([])\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + } + ] +} \ No newline at end of file From 918dedd59bbef48b979cff466d9e217da14fcf28 Mon Sep 17 00:00:00 2001 From: Pratik Watwani Date: Fri, 7 Feb 2025 11:47:35 -0500 Subject: [PATCH 3/3] DI file added Dunn Index visualization file --- book/figures/Dunn_Index_Visualized.png | Bin 0 -> 89836 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 book/figures/Dunn_Index_Visualized.png diff --git a/book/figures/Dunn_Index_Visualized.png b/book/figures/Dunn_Index_Visualized.png new file mode 100644 index 0000000000000000000000000000000000000000..19e71b13f27cfb2a8dc282de3c4046e0697a3c19 GIT binary patch literal 89836 zcmb@ubyQVr`!0t?ikf6( zTV9iqZ5rLN4L@o2S-XgTN#8zo>9&@&`E4g7J2NshquVx?*0(LM8y|2qv$MZ$Z6(4l zB*-twci`IX+cx&n0s^=G*Wci`wzCijw!379PuXd6R@a`4jM|9!XVY7S#Oq|6$jFow zk6&<(9`AH=-aGiSa(XiK&z0-(Cr?bCdM7&aed~3)V~TtC@!qklymEfi=UqpXCk>9B zPvB9zlMqIBFyv20-t7A4D7lAQc0AcxHQ8V85D{TvJ`oW!E=wBb<}4MYRQ#XUt^m?o 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