5. Artificial Neural Networks: Predicting Annual Income

Activity 5.01: Training an MLP for Our Census Income Dataset

Solution:

1. Import all the elements required to load and split a dataset, to train an MLP, and to measure accuracy:

   import pandas as pd
   from sklearn.model_selection import train_test_split
   from sklearn.neural_network import MLPClassifier
   from sklearn.metrics import accuracy_score

2. Using the preprocessed Census Income Dataset, separate the features from the target, creating the variables X and Y:

   data = pd.read_csv("census_income_dataset_preprocessed.csv")
   X = data.drop("target", axis=1)
   Y = data["target"]

   As explained previously, there are several ways to achieve the separation of X and Y, and the main thing to consider is that X should contain the features for all instances, while Y should contain the class label of all instances.

3. Divide the dataset into training, validation, and testing sets, using a split ratio of 10...