In this section, we will combine everything we have illustrated so far and create a classifier on the iris dataset.
The iris data set is described in more detail in the Working with Data Sources recipe in Chapter 1, Getting Started with TensorFlow. We will load this data, and do a simple binary classifier to predict whether a flower is the species Iris setosa or not. To be clear, this dataset has three classes of species, but we will only predict whether it is a single species (I. setosa) or not, giving us a binary classifier. We will start by loading the libraries and data, then transform the target accordingly.
First we load the libraries needed and initialize the computational graph. Note that we also load
matplotlib
here, because we would like to plot the resulting line after:import matplotlib.pyplot as plt import numpy as np from sklearn import datasets import tensorflow as tf sess = tf.Session()
Next we load the iris data. We will...