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`label = predict(Mdl,X)`

```
[label,score,cost]
= predict(Mdl,X)
```

returns
a vector of predicted
class label for the predictor data in the table or matrix `label`

= predict(`Mdl`

,`X`

)`X`

,
based on the trained * k*-nearest neighbor classification
model

`Mdl`

.`[`

also
returns:`label`

,`score`

,`cost`

]
= predict(`Mdl`

,`X`

)

A matrix of classification scores (

`score`

) indicating the likelihood that a label comes from a particular class. For-nearest neighbor, scores are posterior probabilities.*k*A matrix of expected classification cost (

`cost`

). For each observation in`X`

, the predicted class label corresponds to the minimum expected classification costs among all classes.

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