Programmers: André Araújo (andre23035@ilum.cnpem.br) and Samira Oliveira (samira23016@ilum.cnpem.br)

Here we have a Python code that, using the sklearn library, has allowed us to train 3 machine learning models for the prediction of laboratory results.

We have made the simplest code to use.

If you don't have a dataset, use our example dataset.

Follow the steps:

1. Run the libraries
2. Run the functions
3. If the libraries and functions run without problems, import your dataset.xlsx or dataset.csv.
4. Now we are going to process your data. Change the variable "df" to the name of your dataset.
5. Change the variable "suas_colunas" to the columns with numbers without commas.
6. Next, the variable "df1_alt1" will remove the columns that you do not use. The variable "df1_alt2" will remove the lines that you do not use.
7. Now change the FEATURES and the TARGETS to the columns you want to use.
8. Finally, check that the lines of code work correctly.
9. In this case, our code has 3 models to do predicts.
10. Use the code with caution and thank you.