 Mullica, Passaic, Rahway, Raritan, Musconetcong, Hudson and Delaware rivers.
There are no doubt many smaller rivers in the Canadian arctic and along the Northern slope of Alaska That flow north. But for a major navigable river the Mackenzie is the big one. On the South Shore of Hudsons bay there will be a number of North flowing Rivers. Along the North Slope of Quebec there will also Be many smaller North flowing rivers.
Rivers, like all other objects, flow downhill. They all take the paths of least resistance. This path thus could take any direction -- east, west, north, south, and many others in between. Rivers that meander may flow in many directions. Where there are low gradients and gentle slopes, some rivers may flow almost in full circles.<gh_stars>0
package com.starboard.items;

import com.starboard.Player;
import com.starboard.util.Sound;

public class HealingItem extends GameItem implements Usable {
    private int healValue;

    // Constructors
    public HealingItem() {
        isPortable = true;
    }

    public HealingItem(String name, boolean isPortable, int healValue) {
        super(name, isPortable);
        this.healValue = healValue;
    }

    public HealingItem(String name, boolean isPortable, int healValue, String description) {
        this(name, isPortable, healValue);
        setDescription(description);
    }

    public HealingItem(String name, boolean isPortable, int healValue, int quantity) {
        this(name, isPortable, healValue);
        setQuantity(quantity);
    }

    public HealingItem(String name, boolean isPortable, int healValue, String description, int quantity) {
        this(name, isPortable, healValue, description);
        setQuantity(quantity);
    }

    public HealingItem(String name, boolean isPortable, int healValue, String description, int quantity, double weight) {
        this(name, isPortable, healValue, description, quantity);
        setWeight(weight);
    }

    @Override
    public void use(Player player) {
        player.changeHp(getHealValue());
        System.out.printf("Healed %d HP.%n", healValue);
        Sound.play(6); // index 6 is file path for healing sound file
        if (getQuantity() > 1) {
            changeQuantity(-1);
        } else if (getQuantity() == 1) {
            player.getInventory().remove(getName());
        }
    }

    public int getHealValue() {
        return healValue;
    }
}<issue_start><issue_comment>Title: [multi-classification] How to handle labels in test set that are unseen in training set?
username_0: When fitting the `lightgbm.LGBMClassifier` model from Python API, I get a `ValueError: y contains previously unseen labels` when some labels are present in the eval set that are not in the training set.

For instance, training set:

feature_a | target_label
------------ | -------------
1 | 'foo'
2 | 'bar'
1 | 'foo'
2 | 'bar'
3 | 'baz'
1 | 'bar'

And test set:

feature_a | target_label
------------ | -------------
2 | 'foo'
3 | 'qux'


The following code:

```python
model = LGBMClassifier(objective='multiclass')
model(X_train, y_train, eval_set=(X_test, y_test), eval_names=['eval'], eval_metric='multiclass', verbose=50)
```

Will lead to this error:

```
ValueError: y contains previously unseen labels: 'qux'
```

I understand technically why this happens (the label encoder, fitted on the training set, doesn't know about `cux`) but I don't understand the rationale behind it — shouldn't it simply consider that a label that is unknown represents a misclassification here? For instance, the model predicted `bar` for this row, and since it encounters something it hasn't seen before, it would simply say "nope, wrong prediction" and call it a day?

Beyond this, I don't understand how to deal with this problem. I don't want to remove the `cux` line from my testing set, because that would artificially bump the testing accuracy. I want the model to consider a misclassification in this example.

Any idea on how to proceed?
<issue_comment>username_0: After a bit of digging, it appears that this is an issue only for the `fit()` method, not for the `predict()`.

I ended up removing the rows with a target label unseen in the training set, and this serves as a good enough eval set during training.<issue_closed>1. graphitem.getobjects only allows to retrieve a graph item with a single specific itemid and graphid. This is utterly useless, I think this method can be removed.
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