Machine Learning Models were applied to predict the mass of the brain based on gender, age ranges, and head size.

Anne Livia

Last update: Feb 2, 2022

Related tags

Deep Learning HumanBrainWeightRegression

Overview

Brain Weight in Humans

Variations of head sizes and brain weights in humans

Kaggle dataset obtained from this link by Anubhab Swain.

Image obtained from Matthew Butler.

Models implemented by Anne Livia.

Context

This dataset was compiled using a medical study conducted on a group of people.

Content:

This dataset shows a few variations of head sizes and masses of brains, it also consists additional gender and age group columns.

Gender: 1 for Male, 2 for Female
Age Range: 1 represents > 18 years of age, 2 represents < 18 years of age
Head Size(cm^3): Head volume in cubic centimetres
Brain Weight(grams): - Mass of brains in grams

Question to be answered:

Predict the masses of the brains using the data, and later compare it with the actual masses of brains mentioned in the dataset.

Software Information

Python
Pandas
Scikit-learn
Matplotlib
Seaborn

Trained Models

Linear Regression:
- R2 (only Head Size(cm^3) considered) = 0.73
- R2 (All three attributes) = 0.74
Multi-layer Perceptron:
- R2 (All three attributes) = 0.74
Decision Tree:
- R2 (All three attributes) = 0.69

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Machine Learning Models were applied to predict the mass of the brain based on gender, age ranges, and head size.

Related tags

Overview

Brain Weight in Humans

Variations of head sizes and brain weights in humans

Kaggle dataset obtained from this link by Anubhab Swain.

Image obtained from Matthew Butler.

Models implemented by Anne Livia.

Context

Content:

Question to be answered:

Software Information

Trained Models

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