> ## Documentation Index
> Fetch the complete documentation index at: https://kumo.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# loss

#### `loss: <list[str]>` **(Optional)**

## Description

The loss type to use during model optimization depending on the task type.

**Available Options:**

| Task Type                                       | Available loss options                                              |
| :---------------------------------------------- | :------------------------------------------------------------------ |
| Binary Classification/Multilabel Classification | `binary_cross_entropy` (default) <br /> `focal`                     |
| Multiclass Classification                       | `cross_entropy` (default)                                           |
| Regression/Forecasting                          | `mae` <br /> `mse` <br /> `huber` (default) <br /> `multi_quantile` |
| Temporal Link Prediction                        | `cross_entropy` (default)                                           |
| Static Link Prediction                          | `cross_entropy` (default)                                           |
| Multilabel Ranking                              | `cross_entropy` (default)                                           |

By default, `focal` loss uses an `alpha` value of `0.25` (the weighting factor to balance positive vs. negative examples), and a `gamma` value of `2.0` (the balance between easy vs. hard examples). You can further customize this in the model plan by replacing the string by a dictionary:

```
loss:
- name: focal
  alpha: 0.5
  gamma: 4.0
```

By default, `huber` loss uses a delta value of `1.0`. You can further customize this in the model plan by replacing the string by a dictionary:

```
loss:
- name: huber
  delta: 2.0
```

Use `multi_quantile` for regression or forecasting tasks when you want prediction intervals in addition to the median prediction. It trains multiple quantiles with pinball loss and writes `TARGET_PRED` together with 27 quantile columns named `q_0.005`, `q_0.01`, ..., `q_0.995`:

```
loss:
- multi_quantile
```

The full quantile column set is:

```
q_0.005 q_0.01  q_0.02  q_0.025 q_0.05  q_0.1   q_0.15
q_0.2   q_0.25  q_0.3   q_0.35  q_0.4   q_0.45  q_0.5
q_0.55  q_0.6   q_0.65  q_0.7   q_0.75  q_0.8   q_0.85
q_0.9   q_0.95  q_0.975 q_0.98  q_0.99  q_0.995
```

### Supported Task Types

* All