semvec/pypi-packages huggingface dataset:
automate-linear-regression 0.0.1
Linear Regression Automation
Keywords: python,machine learning,machine learning model,regression,linear regression,lasso linear regression,elasticnet linear regression,regularization


# automate-linear-regression

- ### This package is specific to build a Linear Regeression model on the dataset passed as the parameter with its features as well as label to be regressed against. And as such it goes without saying that the analysis and the feature engineering has already been done on the dataset.
    
- ### This package will standardize the data via StandardScaler() so that all features can be on the same scale and obviously so that the model optimization could increase.

- ### Accuracy of the model built by this pacakage is computed using `adjusted R-squared`.

- ### User will also have the flexibility of building the model with regularization modes viz. `Lasso (L1`, `Ridge (L2)` and `ElasticNet` and to compare their accuracies accordingly.


```python
from automateLinearRegression import automate

df        # the dataset you want to build the model of
features  # df's features
label     # df's label

linear_model = automate(df, features, label)
linear_model.split(testSize = 0.15) # first and foremost step is to split the features and label into train and test subdata
linear_model.build()
print(linear_model.accuracy()) # will print the accuracy computed using adjusted R-squared
```


```python
### if the user desiresw to build the model using regularization

linear_model.buildLasso()                # or linear_model.buildRidge or linear_model.buildElasticNet
print(linear_model.accuracy(mode="L1"))  # or mode="L2" or mode="Elastic"
```


```python
linear_model.predict(test_input, mode="L1") # to yield the prediction outcome
```
isqCore 0.3
isq quantum kernel

# isq-qcis python cor


isQ-core是为qcis指令集定制化开发的量子编程语言，以python包的形式提供服务。目前isQ-core python包仍在测试阶段，可通过源码进行离线安装。具体的安装使用说明及isQ-core语法说明可详见 [isQ-core python包使用文档](http://www.arclighttest.cn:10088/isq-core/)