Pipeline

Note: This is a README.md boilerplate generated using Kedro 0.18.12.

Overview

This pipeline:

1. splits the data into training dataset and testing dataset using a configurable ratio found in conf/base/parameters.yml
2. runs a simple 1-nearest neighbour model (make_prediction node) and makes prediction dataset
3. reports the model accuracy on a test set (report_accuracy node)

Pipeline inputs

example_iris_data

Type	pandas.CSVDataSet
Description	Example iris data containing columns

parameters

Type	dict
Description	Project parameter dictionary that must contain the following keys: train_fraction (the ratio used to determine the train-test split), random_state (random generator to ensure train-test split is deterministic) and target_column (identify the target column in the dataset)

Pipeline intermediate outputs

X_train

Type	pandas.DataFrame
Description	DataFrame containing train set features

y_train

Type	pandas.Series
Description	Series containing train set target.

X_test

Type	pandas.DataFrame
Description	DataFrame containing test set features

y_test

Type	pandas.Series
Description	Series containing test set target

y_pred

Type	pandas.Series
Description	Predictions from the 1-nearest neighbour model

Pipeline outputs

None