I want help with understanding of the project, how each class should be implemented and maybe how to design each class, a clue for each class and i should be good

Background: A data back-end stores and gives access to data. For this project you will create a data back-end that enables activity prediction. A simple but widely used machine leaming data set answers the question "should I play tennis today?" The included file's contents are below: errelation weather Gattribute outlook (sunny, overcast, rafny) Battribute temperature real gattribute humidity real gattribute windy (TRUE, FAISE) Qattribute play (yes, no) (4)ata sunny, 85,85, FALSE, no sunny, 80, 90, TRUE, no overcast, 83, 86, FALSE, yes rainy, 70, 96, FALSE, yes rainy, 68,80 , FALSE, yes rainy, 65,70 , TRUE, no overcast, 64,65 , TRUE, yes sunny, 72, 95, FALSE, no sunny, 69, 70, FALSE, yes rainy, 75, 80, FALSE, yes sunny, 75, 70, TRUE, yes overcast, 72, 90, TRUS, yes overcast, 81,75, FALSE, yes rainy, 71, 91, TRUE, no The file is described as follows: (arelation line: title n@ attribute lines: description of each of the n columns in each line of the @ data section. Typically the last attribute is called the "Class" attribute and is the prediction given the other attributes. Your program can ignore all of these lines @ data lines: (called instances). Each line below @ data is one example of known data. In this dataset, the decision a person made about playing tennis, given the specific weather conditions. This project will have two main functions. Using will query known instances given specific values for the attributes to predict what the user should do. For example, if it is sunny, 74 degrees, 69% humidity and windy the system might tell the user they should play tennis ("yes"). Updating will allow new data to be added to the predictor. For example, sunny, 80 degrees, 80% humidity, windy, yes could be added to the collection of instances. For a maximum score of 85% : Play tennis only. You will keep the data as binary: \&ateribute play (yes, no). This means the user is only asking should I play tennis under today's conditions. Using will use input values for each attribute except the class attribute and look at the known data. It will return a value for play. Updating will update the data with additional instances