Effective Mid-Day Meal Analysis Depending on Children’s Needs using Machine Learning

Using state-level knowledge on India’s Mid-Day Meal program our study tends to scrutinize if funds disbursed, and food ingredients equipped for the aim will really function as smart determinants of a variety of kids coated (fed) by the scheme. The influence of food (protein) equipment has a statistically significant impact on the variable amount, according to the study, but the statistical analysis of funds/money disbursed is also of utmost relevance. Analysis and prediction performance of regression models associated in nursing covariates ingredients is vital. Analysis of food ingredients along with Milk as an important component which is sectioned in primary and upper primary class is the approach of this study. To distribute the food according to the child’s needs is crucial. In order to do that, the food requirement of every child needs to be understood and needs to be considered. K-Nearest Neighbour classifier was trained to predict what should be the amount of protein a child has to have in a meal. Similarly, another Logistic Regression model was trained as well in order to predict if the child is gaining from the food served or not. To check the quality of food, in this study rice, wheat and dry beans has been considered and various parameters for instance the area, perimeter, etc. have been taken into consideration in order to check if the supply of food ingredients by the government is up to mark or it still has some improvements to do.