chemfusekit: Data Fusion and Analysis in Colab

A minimal Python / Jupyter Notebook / Colab library for data fusion and chemometrical analysis.

Developed as Federico Aguzzi's Computer Engineering undergraduate thesis project, under the supervision of Software Engineering Professor Angelo Michele Gargantini, based on the scripts made by Dr Giorgio Felizzato and the research of Professor Francesco Saverio Romolo of the Law Department of the University of Bergamo. Further info on the project here.

Get it on pip:

pip install chemfusekit

You can also try this demo:

and find instructions here.

Features

• data fusion: join data from different sensors to increase the quality and precision of your chemometrical analysis
• model training: train, save and load statistical models
• data classification: use your models to classify and predict

Here's a list of the currently available modules:

• LLDF: Low-Level Data Fusion
• PCA: Principal Component Analysis
• LDA: Linear Discriminant Analysis (demo)
• SVM: Support Vector Machine (demo)
• LR: Logistic Regression (demo)
• KNN: k_Neighbors Analysis (demo)
• PLSDA: Partial Least Squres Discriminant Analysis (demo)