Please I have this diabetes dataset which i have cleaned using Altery designer, and I would love to build ML models(Random Forest tree, Logistic regression, KNN, Support Vector Machine and Naive Baye algorithms on it.). I am new to Julia and the MLJ package. Please how can I go about to build my models(and evaluate its accuracy and performance)
-Showing me how to do it with just one or two chosen algorithms will go a long way to help please.
using Pkg Pkg.add("CSV") Pkg.add("DataFrames") using DataFrames using CSV diabetes= CSV.read("diabetes.csv", DataFrame) using Pkg using Pkg; Pkg.activate("my_MLJ_env", shared=true) Pkg.add("MLJ") using MLJ models() Pkg.add("MLJDecisionTreeInterface") diabetes_x= Matrix(diabetes[:,[1,2,3,4,5,6,7,8]]); diabetes_y=diabetes[:, 9]; tree_model = @load RandomForestClassifier pkg=DecisionTree
Please how do I apply that to my dataset? I would have loved to include the dataset