Provides illustration of doing cluster analysis with R.
R code: https://github.com/bkrai/Top-10-Machine-Learning-Methods-With-R
Data file link and more on cluster analysis: https://youtu.be/otjWCaMcVaA
Cluster analysis is a statistical technique used to group similar objects or data points based on their characteristics. The goal is to identify patterns or structures within data without any prior knowledge of the groups. By measuring the similarity or distance between objects, cluster analysis divides the data into distinct clusters where members of each cluster are more similar to one another than to members of other clusters. This method is widely used in various fields such as marketing for customer segmentation, biology for classifying species, and machine learning for exploratory data analysis.
For citation as reference in a research paper, use:
Meshram, A., and Rai, B. (2019). “User-Independent Detection for Freezing of Gait in Parkinson’s Disease Using Random Forest Classification,” International Journal of Big Data and Analytics in Healthcare, Vol. 4, Issue 1, 57-72.
Rai BK (2017) “Feature Selection and Predictive Modeling of Housing Data Using Random Forest,” International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, Vol. 11, No. 4, 880-884.
Xiaoling, Lu., Rai, B., Yan, Z., and Li, Y. (2018). “Cluster-based Smartphone Predictive Analytics for Application Usage and Next Location Prediction,” International Journal of Business Intelligence Research, Vol. 9, No. 2, 64-80.
Topics
00:00 Read data file
00:45 Scatter plot
02:30 Data normalization
04:27 Calculate Euclidean distance
05:54 Cluster dendrogram with complete linkage
08:20 Cluster dendrogram with average linkage
08:52 Cluster membership
10:47 Cluster means
12:35 Silhouette plot
13:31 Scree plot
14:47 Non-hierarchical k-means clustering & interpretation
Cluster analysis is an important tool related to analyzing big data or working in data science field.
Machine Learning videos: https://goo.gl/WHHqWP
Becoming Data Scientist: https://goo.gl/JWyyQc
Introductory R Videos: https://goo.gl/NZ55SJ
Deep Learning with TensorFlow: https://goo.gl/5VtSuC
Image Analysis & Classification: https://goo.gl/Md3fMi
Text mining: https://goo.gl/7FJGmd
Data Visualization: https://goo.gl/Q7Q2A8
Playlist: https://goo.gl/iwbhnE
R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.