j143 commented on a change in pull request #950:
URL: https://github.com/apache/systemml/pull/950#discussion_r435903926
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File path: dev/docs/builtins-reference.md
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@@ -503,3 +504,44 @@ numClasses = 5
X = round(rand(rows = 10, cols = 10, min = 1, max = numClasses))
y = toOneHot(X,numClasses)
```
+
+## `gridSearch`-Function
+
+The `gridSearch`-function is used to find the optimal hyperparameters of
+a model which results in the most ‘accurate’ predictions.
+This function takes train and eval functions by name as well as lists of
+parameter names and vectors of their values, and returns the parameter
+combination and model that gave the best results.
+
+### Usage
+```r
+gridSearch(X, y, train, predict, params, paramValues, verbose = TRUE)
+
+```
+
+### Arguments
+| Name | Type | Default | Description |
+| :------ | :------------- | -------- | :---------- |
+| X | Matrix[Double] | required | Input Matrix of vectors. |
+| y | Matrix[Double] | required | Input Matrix of vectors. |
+| train | String | required | Specified training function. |
+| predict | String | required | Evaluation based function. |
+| params | List[String] | required | List of parameters |
+| paramValues | List[Unknown] | required | Range of values for the
parameters |
+| verbose | Boolean | `TRUE` | If `TRUE` print messages are
activated |
+
+### Returns
+| Type | Description |
+| :------------- | :---------- |
+| Matrix[Double] | Parameter combination |
+| Frame[Unknown] | Best results model |
+
+### Example
+```r
+X = rand (rows = 50, cols = 10)
+y = X %*% rand(rows = ncol(X), cols = 1)
+params = list("reg", "tol", "maxi")
+paramRanges = list(10^seq(0,-4), 10^seq(-5,-9), 10^seq(1,3))
+[B, opt]= gridSearch(X=X, y=y, train="lm", predict="lmPredict", params=params,
paramValues=paramRanges, verbose = TRUE)
Review comment:
Is this not easier to `python` script? :smile:
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