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---
2022-08-28 14:53:34 +00:00
slug: /en/sql-reference/aggregate-functions/reference/stochasticlogisticregression
sidebar_position: 222
---
2022-06-02 10:55:18 +00:00
# stochasticLogisticRegression
This function implements stochastic logistic regression. It can be used for binary classification problem, supports the same custom parameters as stochasticLinearRegression and works the same way.
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### Parameters
Parameters are exactly the same as in stochasticLinearRegression:
`learning rate`, `l2 regularization coefficient`, `mini-batch size`, `method for updating weights`.
For more information see [parameters](#agg_functions-stochasticlinearregression-parameters).
``` text
stochasticLogisticRegression(1.0, 1.0, 10, 'SGD')
```
**1.** Fitting
<!-- -->
See the `Fitting` section in the [stochasticLinearRegression](#stochasticlinearregression-usage-fitting) description.
Predicted labels have to be in \[-1, 1\].
**2.** Predicting
<!-- -->
Using saved state we can predict probability of object having label `1`.
``` sql
WITH (SELECT state FROM your_model) AS model SELECT
evalMLMethod(model, param1, param2) FROM test_data
```
The query will return a column of probabilities. Note that first argument of `evalMLMethod` is `AggregateFunctionState` object, next are columns of features.
We can also set a bound of probability, which assigns elements to different labels.
``` sql
SELECT ans < 1.1 AND ans > 0.5 FROM
(WITH (SELECT state FROM your_model) AS model SELECT
evalMLMethod(model, param1, param2) AS ans FROM test_data)
```
Then the result will be labels.
`test_data` is a table like `train_data` but may not contain target value.
**See Also**
- [stochasticLinearRegression](../../../sql-reference/aggregate-functions/reference/stochasticlinearregression.md#agg_functions-stochasticlinearregression)
- [Difference between linear and logistic regressions.](https://stackoverflow.com/questions/12146914/what-is-the-difference-between-linear-regression-and-logistic-regression)