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ACCURACY

Take two dataframes with the true and predicted labels from a classification task, and indicates whether the prediction was correct or not.These dataframes should both be single columns.Params:true_label : optional strtrue label users can select from original datapredicted_label : optional strresulting predicted label users can selectReturns:out : DataFrameThe input predictions dataframe, with an extra boolean column "prediction_correct".
Python Code
from typing import Optional

from flojoy import DataFrame, flojoy


@flojoy
def ACCURACY(
    true_data: DataFrame,
    predicted_data: DataFrame,
    true_label: Optional[str] = None,
    predicted_label: Optional[str] = None,
) -> DataFrame:
    """Take two dataframes with the true and predicted labels from a classification task, and indicates whether the prediction was correct or not.

    These dataframes should both be single columns.

    Parameters
    ----------
    true_label : optional str
        true label users can select from original data
    predicted_label : optional str
        resulting predicted label users can select

    Returns
    -------
    DataFrame
        The input predictions dataframe, with an extra boolean column "prediction_correct".
    """

    true_df = true_data.m
    predicted_df = predicted_data.m

    # if users prov
    if true_label:
        true_label = true_df[true_label]
    else:
        true_label = true_df.iloc[:, 0]

    if predicted_label:
        predicted_label = predicted_df[predicted_label]
    else:
        predicted_label = predicted_df.iloc[:, 0]

    predicted_df["prediction_correct"] = true_label == predicted_label

    return DataFrame(df=predicted_df)

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Example

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React Flow mini map

In this example, the iris dataset is split into two parts, one for training and the other for testing. The labels from the test data are stripped using an EXTRACT_COLUMNS node, taking only the features of the data.

The true labels are also extracted with another EXTRACT_COLUMNS to be passed to the the ACCURACY node, along with the SUPPORT_VECTOR_MACHINE predictions.

In the output, we see that the SUPPORT_VECTOR_MACHINE has made correct predictions for all of the test data.