List of drinks that generally contains caffeine. Some instances are not drinks exactly. Ground coffee or tea leafs would produce that amount of Volume (ml) if prepared according to the provider. They don't have calories since you can control the sugar level.
Atributes drink: Drink's name. Volume (ml): Volume quantity. Calories: Calories quantity. Caffeine (mg): Caffeine quantity. type: Drink's type. (Coffe, Energy Drinks, Energy Shots, Soft Drinks, Tea, Water)
source: (https://www.kaggle.com/heitornunes/caffeine-content-of-drinks/download) The 5 class labels are:
drink: Name of the drink Volume (ml): Quantity of the drink in mililitres
Calories: in Calories, quantity of the drink
Caffeine (mg): Caffeine quantity in miligrams
type: tea, coffee, energy drink, soft drink, energy shots
Decision Tree
Decision Trees are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features. A tree can be seen as a piecewise constant approximation. Decision trees use multiple algorithms to decide to split a node into two or more sub-nodes. The creation of sub-nodes increases the homogeneity of resultant sub-nodes. Purity of the node increases with respect to the target variable. The decision tree splits the nodes on all available variables and then selects the split which results in most homogeneous sub-nodes..
Naive Bayes Naive Bayes classifiers are a collection of classification algorithms based on Bayes’ Theorem. It is not a single algorithm but a family of algorithms where all of them share a common principle, i.e. every pair of features being classified is independent of each other. It is a probabilistic classifier, which means it predicts on the basis of the probability of an object. Bayes' theorem is also known as Bayes' Rule or Bayes' law, which is used to determine the probability of a hypothesis with prior knowledge. It depends on the conditional probability.
Good ideas or strategies that you were not able to implement which you think can help improve performance.