SVM Classification
Support Vector Machine (SVM) is a popular supervised machine learning algorithm used for classification tasks. It works by finding the optimal hyperplane that separates different classes of data points in the feature space.
Method: POST Authorization: API Keyhttps://engine.raccoon-ai.io/api/v1/ml/classification/svm
Authorization
Type | Key | Value |
---|---|---|
API Key | X-Api-Key | rae_###### |
Request Body
Section | Key | Data Type | Required | Description |
---|---|---|---|---|
train | data | json | true | Data that use to train the model |
features | list | true | Input features (X) | |
targets | list | true | Output targets (y) | |
config | json | false | Train configurations | |
predict | data | json | true | Data that need to predicted by the trained model |
config | json | false | Predict configurations |
Types
{
"train" : {
"data" : <json_data>,
"features": <list>,
"targets" : <list>,
"config" : {
"std_scale": <boolean>,
"encoder" : <"label" | "drop">,
"val_size" : <float>
}
},
"predict": {
"data": <json_data>,
"config": {
"include_inputs": <boolean>,
"round": <int>
}
}
}
Sample
{
"train": {
"data": {
"R&D Spend": {
"0": 165349.2,
"1": 162597.7,
"2": 153441.51,
"3": 144372.41,
"4": 142107.34,
"5": 131876.9,
"6": 134615.46,
"7": 130298.13,
"8": 120542.52,
"9": 123334.88
},
"Administration": {
"0": 136897.8,
"1": 151377.59,
"2": 101145.55,
"3": 118671.85,
"4": 91391.77,
"5": 99814.71,
"6": 147198.87,
"7": 145530.06,
"8": 148718.95,
"9": 108679.17
},
"Marketing Spend": {
"0": 471784.1,
"1": 443898.53,
"2": 407934.54,
"3": 383199.62,
"4": 366168.42,
"5": 362861.36,
"6": 127716.82,
"7": 323876.68,
"8": 311613.29,
"9": 304981.62
},
"State": {
"0": "New York",
"1": "California",
"2": "Florida",
"3": "New York",
"4": "Florida",
"5": "New York",
"6": "California",
"7": "Florida",
"8": "New York",
"9": "California"
},
"Profit": {
"0": 192261.83,
"1": 191792.06,
"2": 191050.39,
"3": 182901.99,
"4": 166187.94,
"5": 156991.12,
"6": 156122.51,
"7": 155752.6,
"8": 152211.77,
"9": 149759.96
}
},
"features": ["R&D Spend", "Administration", "Marketing Spend", "Profit"],
"targets": ["State"],
"config": {
"std_scale": true,
"encoder": "label"
}
},
"predict": {
"data": {
"R&D Spend": {
"0": 165349.2,
"1": 162597.7
},
"Administration": {
"0": 136897.8,
"1": 151377.59
},
"Marketing Spend": {
"0": 471784.1,
"1": 443898.53
},
"Profit": {
"0": 471784.1,
"1": 443898.53
}
},
"config": {
"include_inputs": true,
"round": 2
}
}
}
Reponse Body
Key | Data Type | Description |
---|---|---|
success | boolean | Indicate the success of the request |
msg | string | Message indicators |
error | string | Error information, only set if success is false |
result | json | Result, only set if success is true |
score | json | Accuracy scores of the training and testing phases, only set if success is true |
generated_ts | float | Generated timestamp |
Types
{
"success": <boolean>,
"msg": <string>,
"error": <string>,
"result": <json>,
"score": {
"train": <float>,
"test": <float>
},
"generated_ts": <timestamp>
}
Sample
{
"success": true,
"msg": "Model trained and predicted successfully",
"error": null,
"result": {
"R&D Spend": {
"0": 165349.2,
"1": 162597.7
},
"Administration": {
"0": 136897.8,
"1": 151377.59
},
"Marketing Spend": {
"0": 471784.1,
"1": 443898.53
},
"Profit": {
"0": 190209.72,
"1": 186863.18
},
"State": {
"0": "New York",
"1": "California"
}
},
"score": {
"train": 0.942446542689397,
"test": 0.9649618042060305
},
"saved_in": null,
"generated_ts": 1685439220.425382
}