52 lines
2.0 KiB
Markdown
52 lines
2.0 KiB
Markdown
|
Install required dependencies for matplotlib GUI frontend and all pip other packages for this project
|
||
|
|
||
|
```bash
|
||
|
sudo apt install python3-tk
|
||
|
python3.9 -m pip install -r requirements.txt
|
||
|
```
|
||
|
|
||
|
Given a set of tuple `(X,Y)` data points as `[(X, Y), .., (X, Y)]`, determine the
|
||
|
best fitting line plot, and then apply this projection to predict the dependent `Y`
|
||
|
value using an independent `GIVEN_X` value.
|
||
|
|
||
|
```bash
|
||
|
python3.9 linear-regression.py -h
|
||
|
usage: linear-regression.py [-h] [--silent] [--file [FILE_PATH]] [GIVEN_X] [X,Y ...]
|
||
|
|
||
|
Find most fitting line plot for given data points and predict value given some X
|
||
|
|
||
|
positional arguments:
|
||
|
GIVEN_X Value for X for prediction using linear regression
|
||
|
(default: '4.5')
|
||
|
|
||
|
X,Y A list of data points separated by spaces as: x,y x,y x,y ...
|
||
|
(default: '[(1, 3), (2, 7), (3, 5), (4, 9), (5, 11), (6, 12), (7, 15)]')
|
||
|
|
||
|
|
||
|
optional arguments:
|
||
|
-h, --help show this help message and exit
|
||
|
--silent When this flag is set, line plot visualization will not be shown
|
||
|
(default: 'False')
|
||
|
|
||
|
--file [FILE_PATH], -f [FILE_PATH]
|
||
|
Optionally provide file for data to be read from. Each point must be on it's own line with format x,y
|
||
|
```
|
||
|
|
||
|
By default, the following linear regression is calculated and displayed
|
||
|
```bash
|
||
|
python3.9 linear-regression.py
|
||
|
|
||
|
|
||
|
Finding fitting line plot for given data [(1, 3), (2, 7), (3, 5), (4, 9), (5, 11), (6, 12), (7, 15)]
|
||
|
points_avg: (4.0, 8.857142857142858)
|
||
|
variance: (28.0, 104.85714285714286)
|
||
|
sigma: (2.160246899469287, 4.180453381654971)
|
||
|
covariance: 8.666666666666666
|
||
|
correlation: 0.9596775116832306
|
||
|
Our line Y = BX + A must pass through the point (4.0, 8.857142857142858)
|
||
|
Y = (1.8571428571428565)X + 1.4285714285714315
|
||
|
For X = 4.5, Y is predicted to be 9.785714285714285
|
||
|
```
|
||
|
|
||
|
![](screenshot.png)
|