new Bot(networkopt, optionsopt)
Parameters:
| Name |
Type |
Attributes |
Description |
network |
Network
|
<optional>
|
|
options |
Object
|
<optional>
|
Properties
| Name |
Type |
Attributes |
Description |
_dataset |
Dataset
|
<optional>
|
Testing dataset |
dataset |
Dataset
|
<optional>
|
Training dataset |
|
- Source:
Methods
(static) fromDataset(dataset, optionsopt) → {Bot}
Parameters:
| Name |
Type |
Attributes |
Description |
dataset |
Dataset
|
|
|
options |
Object
|
<optional>
|
Properties
| Name |
Type |
Attributes |
Default |
Description |
train |
boolean
|
number
|
<optional>
|
1
|
Will train bot for options.train iterations before creating it |
test |
number
|
<optional>
|
0
|
Will use options.test ratio (e.g. 0.2 === 20%) of the dataset for testing the bot's accuracy |
shuffle |
boolean
|
<optional>
|
false
|
Iff true, the dataset will be shuffled before splitting the dataset or training the bot. |
|
- Source:
Returns:
-
Type
-
Bot
(static) fromJSON(json, options)
Parameters:
| Name |
Type |
Description |
json |
Array.<Object>
|
|
options |
Object
|
Properties
| Name |
Type |
Description |
test |
number
|
Ratio of dataset to test (e.g. 0.2 is 20%) |
outputs |
Array.<string>
|
JSON Keys which hold "outputs" desired outputs - bots will try to mimic or recreate these keys given all the other keys in the objects given |
|
- Source:
Example
const dataset = require("@liquid-carrot/data.cjyvyspsy0000l2m932iv07k1");
const bot = Bot.fromJSON(dataset, {
outputs: ["quality"],
test: 0.2 // 20% of data will used for testing, not training
})
(static) fromPath()
- Source:
Examples
JSON
const bot = Bot.fromPath("./data.train.json");
bot.test(dataset); // { error: 0.01457, accuracy: 96.453%, fitness: 34.3412 }
CSV
const bot = Bot.fromPath("./data.train.csv", { outputs: ["age", "height"] });
bot.test(dataset); // { error: 0.01457, accuracy: 96.453%, fitness: 34.3412 }
XML
const bot = Bot.fromPath("./data.train.xml");
bot.test(dataset); // { error: 0.01457, accuracy: 96.453%, fitness: 34.3412 }
(static) fromString()
- Source:
Example
Advanced CSV - White Wine Quality
const dataset = require("data.cjyvyspsy0000l2m932iv07k1");
const bot = Bot.fromString(dataset, {
type: "csv",
headers: true,
outputs: ["quality"],
delimeter: ";",
test: 0.2 // 20% of data will used for testing, not training
});
bot.test(); // { error: 0.01457, accuracy: 96.453%, fitness: 34.3412 }
(static) fromURL(url, optionsopt)
Parameters:
| Name |
Type |
Attributes |
Description |
url |
string
|
|
|
options |
Object
|
<optional>
|
|
- Source:
Example
const bot = Bot.fromURL(https://liquidcarrot.io/dataset/monkeys.csv)
test(options) → {number}
Test the bots performance on the test dataset
Parameters:
| Name |
Type |
Description |
options |
Object
|
Properties
| Name |
Type |
Attributes |
Default |
Description |
accuracy |
boolean
|
<optional>
|
false
|
Iff true, returns model accuracy instead of error |
round |
boolean
|
<optional>
|
false
|
Iff true, rounds the output when testing |
|
- Source:
Returns:
Returns the average error on the test dataset
-
Type
-
number