# Feature Importance

**Module:** `sovai.extensions.feature_importance`

## Functions

### `random_projection_importance()`

```python
def random_projection_importance(df_filled, n_components = 100)
```

***

### `fast_nonlinear_diverse_selector()`

```python
def fast_nonlinear_diverse_selector(df_valid, n_components = 100, gamma = 1.0)
```

***

### `fast_ica_selector()`

```python
def fast_ica_selector(df_filled, n_components = 20)
```

***

### `truncated_svd_selector()`

```python
def truncated_svd_selector(df_filled, n_components = 20)
```

***

### `sparse_random_projection_selector()`

```python
def sparse_random_projection_selector(df_returns, n_components = 30)
```

***

### `pca_varimax_selection()`

```python
def pca_varimax_selection(df_returns, k = 30, n_components = 50)
```

***

### `pca_varimax_rolling_stats()`

```python
def pca_varimax_rolling_stats(df_returns, k = 30, window = 30, n_components = 50)
```

***

### `diverse_stock_selector()`

```python
def diverse_stock_selector(df_returns, n_components = 30, n_clusters = 20)
```

***


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