Table 7 Important coefficients in each category with machine learning methods
From: Association of dietary intake and cervical cancer: a prevention strategy
Target category | Variable’s name | Coefficients of each variable | Performance of model |
|---|---|---|---|
Important micronutrients identified by deep learning | Phosphorus (mg) | 1 | MSE: 0.036 R2: 0.855 AUC: 0.993 Accuracy:96.31 |
Selenium | 0.981 | ||
Iron (mg) | 0.877 | ||
Zinc | 0.860 | ||
Niacin (mg) | 0.824 | ||
Thiamin (mg) | 0.818 | ||
Folate | 0.793 | ||
Vitamin B6 (mg) | 0.789 | ||
Calcium (mg) | 0.784 | ||
Potassium (mg | 0.750 | ||
Cooper | 0.721 | ||
Iodin | 0.721 | ||
Chloride | 0.712 | ||
VitaminD | 0.688 | ||
Carotene | 0.673 | ||
Important macronutrients and other nutrient factors identified by deep learning | Polyunsaturated fatty acid | 1.000 | MSE: 0.016 R2: 0.935 AUC: 0.999 Accuracy:98.80 |
Salt | 0.963 | ||
Milk | 0.868 | ||
Snacks | 0.861 | ||
dietary fiber | 0.860 | ||
WholeBread | 0.824 | ||
Legumes | 0.798 | ||
Yogurt | 0.722489 | ||
Tot.N2g | 0.712064 | ||
Tea | 0.701140 | ||
Starch | 0.671164 | ||
Sugar | 0.663765 | ||
protein.g | 0.586717 | ||
Important sexual factor identified by decision tree | Age first sex Menstrual disorder Number of sex | Accuracy: 99.66 | Â |
Important demographic factors identified by decision tree | Marriage,education | Accuracy: 99.90 | Â |
Important medical examination factors identified by decision tree | Smear Exocervix Hpv-cat Wart Hpv-positive | Accuracy: 98.47 | Â |