Clustering Electricity Consumption Profiles

Job ID: 38740425

Budget: €30 – €250 EUR

I'm seeking an expert in data analysis and machine learning to help me cluster electricity consumption profiles. The primary goal of this project is to compare different clustering methods using CVI's (silhoutte index, Davies-Bouldin Index, and Calinski-Harabasz Index). I already have a working code that clusters the load profiles per household using k-means. I would like to add on to the model by comparing different clustering techniques, and different types of normalization. I would like the output of the model to be a table of the CVI's per household cluster, comparing different clustering methods.

Key Responsibilities:
- Utilize various clustering techniques including K-means, Hierarchical, Fuzzy c-means, and Self-Organizing Maps (SOM).

Ideal Candidate:
- Proficient in data analysis and machine learning in Python.
- Experienced with the specified clustering techniques.
Related categories: Algorithm Machine Learning (ML) Data Science