Artificial Intelligence By Example

Test dataset and prediction

In this case, the test dataset has two main functions. First, some test data confirms the prediction level of the trained and now-labeled dataset. The input contains random distances and locations. The following code implements the output that predicts which cluster the data points will be in:

#VI.Test dataset and predictionx_test = [[40.0,67],[20.0,61],[90.0,90],[50.0,54],[20.0,80],[90.0,60]]prediction = kmeans.predict(x_test)print("The predictions:")print (prediction)'''Output of the cluster number of each example[3 3 2 3 3 4]'''

The second purpose, in future, will be to enter new warehouse data for decision-making purposes, as explained in the next section.