wizard-420 commented on a change in pull request #952:
URL: https://github.com/apache/systemml/pull/952#discussion_r436240465
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File path: dev/docs/builtins-reference.md
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@@ -318,7 +320,47 @@ slicefinder(X,W, y, k, paq, S);
### Usage
```r
X = rand (rows = 50, cols = 10)
-y = X %*% rand(rows=ncol(X), 1)
+y = X %*% rand(rows = ncol(X), cols = 1)
w = lm(X = X, y = y)
ress = slicefinder(X = X,W = w, Y = y, k = 5, paq = 1, S = 2);
```
+
+## `confusionMatrix`-Function
+
+A `confusionMatrix` is a technique for summarizing the performance of a
classification algorithm.
+Calculating a confusion matrix can give you a better idea of what your
classification model is getting right and what types of errors it is making.
+This confusionMatrix function accepts two matrices with one column each, these
two matrices are vector for prediction and one-hot-encoded matrix respectively.
+Then it computes the max value of each vector and compare them, after whichit
calculates and returns the sum of classifications and the average of each true
class.
+
+### Usage
+```r
+confusionMatrix(P,Y)
+```
+
+### Arguments
+
+| Name | Type | Default | Description |
+| :------ | :------------- | :--- | :---------- |
+| P | Matrix[Double] | --- |vector of prediction |
+| Y | Matrix[Double] | --- | vector of Golden standard One
Hot Encoded|
+
+### Returns
+
+|Name | Type | Description |
+|:-----------------| :------------- | :---------- |
+|ConfusionSum | Matrix[Double] | The Confusion Matrix Sums of
classifications |
+|ConfusionAvg | Matrix[Double] | The Confusion Matrix averages of each
true class|
+
+### Example
+ #here numClasses is assigned to 1 as numClasses is directly proportional to
the
+ number of columns in the one hot data matrix, as confusion matrix accepts
only matrices with one column.
Review comment:
ok I will make all the neccecary changes
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