15RanClassification

Giving a model new inputs

I trained a 1-nearest-neighbour classifier on Iris and showed how to pass one new flower's four measurements to it as a NumPy array.

What it printed in 2022

Numbers read from the saved notebook outputs. Cell numbers count every cell in the notebook, Markdown included, starting at 1.
Output	Value	Cell #
Prediction for the sample flower	Iris-setosa	8

Cell # counts every cell from the top of the notebook, Markdown included, starting at 1.

scikit-learn warned that the new input had no feature names, because the model was trained on a DataFrame. The prediction still worked.

Iris, 150 flowers, from the tutorial author's data repository.

Wrap prediction in a small function that takes named fields and checks their ranges.
Print the test accuracy and its uncertainty before showing off predictions.

23 · 15
InteractiveWeaker than it looked
Thirty flowers cannot tell 93% from 100%
The 1-nearest-neighbour model got 30 of 30 test flowers right, but the 95% interval runs from 88.4% to 100%. Over 1,000 other splits only 23% were perfect.
Read the audit