n Part $2,$ we will use $14$ out of $15$ attributes as predictors describe below to predict if income goes above or below $\backslash$$$50$K$/$yr based on census data. $`$Income$`$ will be the label.

### Data:

An individual$$s annual income results from various factors. Intuitively, it is influenced by the individual$$s education level, age, gender, occupation, and etc.

### Fields:

The dataset contains $15$ columns

#### Target field: Income

$-$ The income is divide into two classes: $50$K

#### Number of attributes: $14$

$--$ These are the demographics and other features to describe a person

We can explore the possibility in predicting income level based on the individual$$s personal information