Regresion logistica en Python | Clasificacion | statsmodels| Cap #4
995 بار بازدید -
4 سال پیش
-
In this new statistical adventure
In this new statistical adventure using Python you will discover a complete statistical analysis of a series of data from patients with heart failure where the objective is to predict whether or not the patient survives given certain attributes such as Age, Sex, Platelet level, ejection fraction of heart, blood pressure, etc.
https://archive.ics.uci.edu/ml/datase...
The tool used for this is logistic regression, a supervised classification algorithm that allows us to better interpret the coefficients obtained than other supervised algorithms.
1. Discussion of the problem
2. What is logistic regression (equations and Odds)
2. Data Loading
3. Exploratory analysis (EDA)
4. Logistic regression model with Scikit Learn (sklearn)
5. Accuracy and cross validation
6. Logistic regression model with statsmodels
7. Model selection
8. Prediction
9. Accuraccy scores for training and testing sets
10. Comparison between sklearn and statsmodels
11. Logistic regression model with GLM (statsmodels
https://archive.ics.uci.edu/ml/datase...
The tool used for this is logistic regression, a supervised classification algorithm that allows us to better interpret the coefficients obtained than other supervised algorithms.
1. Discussion of the problem
2. What is logistic regression (equations and Odds)
2. Data Loading
3. Exploratory analysis (EDA)
4. Logistic regression model with Scikit Learn (sklearn)
5. Accuracy and cross validation
6. Logistic regression model with statsmodels
7. Model selection
8. Prediction
9. Accuraccy scores for training and testing sets
10. Comparison between sklearn and statsmodels
11. Logistic regression model with GLM (statsmodels
4 سال پیش
در تاریخ 1399/04/20 منتشر شده
است.
995
بـار بازدید شده