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import { InferenceOutputError } from "../../lib/InferenceOutputError";
import type { BaseArgs, Options } from "../../types";
import { request } from "../custom/request";
export type TabularRegressionArgs = BaseArgs & {
inputs: {
/**
* A table of data represented as a dict of list where entries are headers and the lists are all the values, all lists must have the same size.
*/
data: Record<string, string[]>;
};
};
/**
* a list of predicted values for each row
*/
export type TabularRegressionOutput = number[];
/**
* Predicts target value for a given set of features in tabular form.
* Typically, you will want to train a regression model on your training data and use it with your new data of the same format.
* Example model: scikit-learn/Fish-Weight
*/
export async function tabularRegression(
args: TabularRegressionArgs,
options?: Options
): Promise<TabularRegressionOutput> {
const res = await request<TabularRegressionOutput>(args, {
...options,
taskHint: "tabular-regression",
});
const isValidOutput = Array.isArray(res) && res.every((x) => typeof x === "number");
if (!isValidOutput) {
throw new InferenceOutputError("Expected number[]");
}
return res;
}