K nearest neighbors classification

We want to classify the Iris dataset using a KNN classifier.

from __future__ import division, unicode_literals

from numpy import array

from gemseo.api import configure_logger, load_dataset
from gemseo.mlearning.api import create_classification_model

configure_logger()

Out:

<RootLogger root (INFO)>

Load Iris dataset

iris = load_dataset("IrisDataset", as_io=True)

Create the classification model

Then, we build the linear regression model from the discipline cache and displays this model.

model = create_classification_model("KNNClassifier", data=iris)
model.learn()
print(model)

Out:

KNNClassifier(n_neighbors=5)
   based on the scikit-learn library
   built from 150 learning samples

Predict output

Once it is built, we can use it for prediction.

input_value = {
    "sepal_length": array([4.5]),
    "sepal_width": array([3.0]),
    "petal_length": array([1.0]),
    "petal_width": array([0.2]),
}
output_value = model.predict(input_value)
print(output_value)

Out:

{'specy': array([0])}