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nityansuman authored Mar 16, 2024
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[Nightly Updated] Lazy Predict 2.0 to help you benchmark models without much code and understand what works better without any hyyper-parameter tuning.

- Free software: MIT license
- Documentation: <https://lazypredict.readthedocs.io>.
# Coming soon

# Installation
- [ ] LLM based task benchmarking
- [ ] Text Classification
- [ ] Token Classification
- [ ] Text Summarization
- [ ] Text Similarity
- [ ] Stats model benchmarking

To install Lazy Predict:
# Getting started

pip install lazypredict-nightly
To install Lazy Predict Nightly:

# Usage
pip install lazypredict-nightly

To use Lazy Predict in a project:

import lazypredict

# Classification

Example :
## Classification

```
# Old Way
from lazypredict.Supervised import LazyClassifier
# New Way
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| ExtraTreeClassifier | 0.922807 | 0.912168 | 0.912168 | 0.922462 | 0.0109999 |
| CheckingClassifier | 0.361404 | 0.5 | 0.5 | 0.191879 | 0.0170043 |
| DummyClassifier | 0.512281 | 0.489598 | 0.489598 | 0.518924 | 0.0119965 |
```

# Regression

Example :
## Regression

```
# Original Way
from lazypredict.Supervised import LazyRegressor
# Alternate Way
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| DummyRegressor | -0.38 | -0.02 | 7.56 | 0.01 |
| LassoLars | -0.38 | -0.02 | 7.56 | 0.01 |
| KernelRidge | -11.50 | -8.25 | 22.74 | 0.01 |


```

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