unaimart ml_acdcproject issues

unaimart / ml_acdcproject

In this project, your aim is to leverage machine learning to automatically classify patients' examinations into five distinct classes using as predictors cardiac magnetic resonance radiomics.

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improve eda with dim reduction, add logic to skip plot generation, add splitting logic, add pipelines and evaluation logic

#16 marcelokscunha closed 2 months ago
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Document - Feature Engineering and Model Enhancement

#15 marcelokscunha opened 3 months ago
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Document - Results Analysis

#14 marcelokscunha opened 3 months ago
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Document - Baseline Model Development

#13 marcelokscunha opened 3 months ago
0
Document - Training and validation set creation

#12 marcelokscunha opened 3 months ago
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Document - Exploratory Data Analysis

#11 marcelokscunha opened 3 months ago
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Results Analysis

#10 marcelokscunha opened 3 months ago
0
Feature Engineering and Model Enhancement

#9 marcelokscunha opened 3 months ago
2
Baseline Model Development - tree-based classifier from scikit-learn

#8 marcelokscunha closed 2 months ago
1
Baseline Model Development - AutoML/H20

#7 marcelokscunha closed 2 months ago
1
Training and validation set creation - (cross-validation).

#6 marcelokscunha closed 2 months ago
1
Training and validation set creation - simple splitting (train/val/test)

#5 marcelokscunha closed 2 months ago
1
EDA - correlations (Pearson, Spearman)

#4 marcelokscunha closed 2 months ago
1
EDA - missing data

#3 marcelokscunha closed 2 months ago
1
EDA - outliers

#2 marcelokscunha closed 2 months ago
1
EDA - feature distributions

#1 marcelokscunha closed 2 months ago
1