> For the complete documentation index, see [llms.txt](https://tusharkolekar24.gitbook.io/package-kolekar-1/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://tusharkolekar24.gitbook.io/package-kolekar-1/welcome-to-package-kolekar/gradient-descent.md).

# Gradient Descent

### LinearRegressionModel

Importing Regression models based on gradient descent concept that can improve prediction accuracy and models performance using `package-Kolekar`.

```python
from package_Kolekar.Gradient_Descent.LinearRegression import LinearRegressionModel
```

Preparing Linear Regression Model  using  `package-Kolekar`

```python
model = LinearRegressionModel(learning_rate=0.3,
                              max_iter=1000)
```

### RidgeRegressionModel

Importing Regression models based on gradient descent concept that can improve prediction accuracy and models performance using `package-Kolekar`.

```python
from package_Kolekar.Gradient_Descent.RidgeRegression import RidgeRegressionModel
```

Preparing Ridge Regression Model  using  `package-Kolekar`

```python
model = RidgeRegressionModel(learning_rate=0.3,
                             max_iter=1000,
                             l2_penalty=1e-10)
```

### LassoRegressionModel

Importing Regression models based on gradient descent concept that can improve prediction accuracy and models performance using `package-Kolekar`.

```python
from package_Kolekar.Gradient_Descent.LassoRegression import LassoRegressionModel
```

Preparing Lasso Regression Model  using  `package-Kolekar`

```python
model = LassoRegressionModel(learning_rate=0.3,
                             max_iter=1000,
                             l1_penalty=0.1)
```

### ElasticNetRegressionModel

Importing Regression models based on gradient descent concept that can improve prediction accuracy and models performance using `package-Kolekar`

```python
from package_Kolekar.Gradient_Descent.ElasticNetRegression import ElasticNetRegressionModel
```

Preparing ElasticNet Regression Model  using  `package-Kolekar`

```python
model = ElasticNetRegressionModel(learning_rate=0.3, 
                                   max_iter=1000,
                                   l1_penalty=0.1,
                                   l2_penalty=1e-10)
```