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### Description:
Our current model scores need improvement ```model/model_selection.ipynb```. Here are the current scores:
- Linear Regression: 0.2667
- Lasso Regression: 0.2744
- Decision Tree: 0…
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We currently use logistic reg for classification and linear reg for regression. I bet lasso would perform better!
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Use L1, L2 and elasticNet Regression to counter overfitting.
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remove tsne plots, they dont add any value
add lasso regression to identify exposures
add look-through to identify exposures
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In terms of functionality, the mid-term end goal is to achieve an offering of ML algorithms and pre-processing routines comparable to what is currently available in Python's [`scikit-learn`](https://s…
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#### Describe the bug
`Ridge.coef_` returns an array with shape `(1, n_features)`, while `Lasso.coef_` returns an array with shape `(n_features,)`. LinearRegression.coef_ resembles Ridge.coef_ …
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A very nice simple example.
https://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-ridge-lasso-regression-python/
Please read before class
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* ROC for LDA
* ROC for Logistic Regression
* RDA ?
* Run Variable Selection - Step, Lasso, PCA
* Scientific Question we are answering??
* Misclassification rate for Indicator portion
*
bms63 updated
7 years ago
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Hi,
I've run hyperopt-sklearn successfully and i really like it. Is it possible to add Logistic Regression, ElasticNet and Lasso regression? I find them a bit difficult to tune sometimes. Thanks!
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### Some of the most common ML Algorithms are listed below. Feel free to suggest other algorithms, not on the list. and we'll update it.
**Name**
- [ ] Multiple Linear Regression
- [ ] Lasso Re…