<commit_before>---
title: Parameter Estimates - Statistics vs. Computer Science 
updated: 2017-04-30 09:35
layout: post
author: <NAME> 
category: Statistics, Computer Science, Learning, Regression
tags: 
- Statistics
- Computer Science
- Learning
- Regression
use_math: true
---

# Statistics vs. Computer Sciecne 

|                      | Statistics | Computer Science   |
|----------------------|------------|--------------------|
| Method               | Algebra    | Update by Learning |
| Parameter(Regression)| OLS        | Delta Rule         |


* Regression by Algebra(Statistics)

Goal: Paramters that minimize OLS(Ordinary Least Squares)

![rss](/result_images/rss.png  "rss")

* Regression by Learning(Computer Science)

Goal: Update parameters that minimize error (Y - Y') given the epochs

![delta](/result_images/delta.png  "delta")

When a = 0.1 and x, y are given, below table shows the procedure of updating parameter 

| data |   | learning |      |                 |    Update   |
|------|---|----------|------|:---------------:|:-----------:|  
| x    | y | w        | y'   | e               |delta_w=a*e*x|
| 2    | 1 | 0.3      | 0.6  | 1 - 0.6 = 0.4   |0.08         |<commit_msg>Update 2017-04-30-stat_vs_cs.md<commit_after>---
title: OLS vs. Learning in Regression Parameter Estimates 
updated: 2017-04-30 09:35
layout: post
author: <NAME> 
category: Statistics, Computer Science, Learning, Regression
tags: 
- OLS
- Learning
- Regression
use_math: true
---

# Statistics vs. Computer Sciecne 

|                      | Statistics | Computer Science   |
|----------------------|------------|--------------------|
| Method               | Algebra    | Update by Learning |
| Parameter(Regression)| OLS        | Delta Rule         |


* Regression by Algebra(Statistics)

Goal: Paramters that minimize OLS(Ordinary Least Squares)

![rss](/result_images/rss.png  "rss")

* Regression by Learning(Computer Science)

Goal: Update parameters that minimize error (Y - Y') given the epochs

![delta](/result_images/delta.png  "delta")

When a = 0.1 and x, y are given, below table shows the procedure of updating parameter 

| data |   | learning |      |                 |    Update   |
|------|---|----------|------|:---------------:|:-----------:|  
| x    | y | w        | y'   | e               |delta_w=a*e*x|
| 2    | 1 | 0.3      | 0.6  | 1 - 0.6 = 0.4   |0.08         |
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