[MINOR][DOCS] Fix all typos in markdown files of `doc` and similar patterns in other comments

## What changes were proposed in this pull request?

This PR tries to fix all typos in all markdown files under `docs` module,
and fixes similar typos in other comments, too.

## How was the this patch tested?

manual tests.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #11300 from dongjoon-hyun/minor_fix_typos.

1 files changed, 3 insertions, 3 deletions

diff --git a/docs/mllib-evaluation-metrics.md b/docs/mllib-evaluation-metrics.md
index 774826c270..a269dbf030 100644
--- a/docs/mllib-evaluation-metrics.md
+++ b/docs/mllib-evaluation-metrics.md
@@ -67,7 +67,7 @@ plots (recall, false positive rate) points.
   </thead>
   <tbody>
     <tr>
-      <td>Precision (Postive Predictive Value)</td>
+      <td>Precision (Positive Predictive Value)</td>
       <td>$PPV=\frac{TP}{TP + FP}$</td>
     </tr>
     <tr>
@@ -360,7 +360,7 @@ $$I_A(x) = \begin{cases}1 & \text{if $x \in A$}, \\ 0 & \text{otherwise}.\end{ca
 
 **Examples**
 
-The following code snippets illustrate how to evaluate the performance of a multilabel classifer. The examples
+The following code snippets illustrate how to evaluate the performance of a multilabel classifier. The examples
 use the fake prediction and label data for multilabel classification that is shown below.
 
 Document predictions:
@@ -558,7 +558,7 @@ variable from a number of independent variables.
       <td>$RMSE = \sqrt{\frac{\sum_{i=0}^{N-1} (\mathbf{y}_i - \hat{\mathbf{y}}_i)^2}{N}}$</td>
     </tr>
     <tr>
-      <td>Mean Absoloute Error (MAE)</td>
+      <td>Mean Absolute Error (MAE)</td>
       <td>$MAE=\sum_{i=0}^{N-1} \left|\mathbf{y}_i - \hat{\mathbf{y}}_i\right|$</td>
     </tr>
     <tr>