Random Forest Classification (ML_CN_7)
This function combines multiple decision trees and aggregates their results to make predictions.
Random Forest is an ensemble machine learning algorithm that combines multiple decision trees to improve performance and reduce overfitting. It creates a set of decision trees by randomly selecting subsets of the features and data samples, and then aggregates the results of the trees to make predictions.
Sample Request
Build a Random Forest Classification model named, "ClassicModel"
Building a Random Forest Classification model
Random Forest Classification
POST
https://autogon.ai/api/v1/engine/start
Request Body
Name | Type | Description |
---|---|---|
project_id* | int | The |
block_id* | int | The |
function_code* | string | The function code for current block |
parent_id* | int | The |
args* | object | Block arguments |
model_name* | String | Name of the model to be used for prediction. |
random_state | int | Seed for random number generation. If provided, it ensures reproducibility of the random processes in the algorithm. If not provided, a random seed will be used |
n_estimators | int | The number of trees in the forest (ensemble) used by the algorithm. Each tree contributes to the final prediction. Larger values generally improve performance, but also increase computation time. |
criterion | String | The function to measure the quality of a split in the decision tree. Common criteria include |
Sample Request
Make predictions with the pre-built model passing an optional test data.
Predicting with Random Forest Classification
Random Forest Classification Predict
POST
https://autogon.ai/api/v1/engine/start
Request Body
Name | Type | Description |
---|---|---|
model_name* | String | Name of previously trained model to be used for prediction |
test_data | String | Input data for prediction. Defaults to |
project_id* | int | ID of the current project |
block_id* | int | ID of the current block |
parent_id* | int | ID of the previous block |
function_code* | String | Function code for the current block |
Sample Request
Evaluate model metrics
Decision Tree Classification Metrics
POST
https://autogon.ai/api/v1/engine/start
Request Body
Name | Type | Description |
---|---|---|
project_id* | int | ID of the current project |
parent_id* | int | ID of the previous block |
block_id* | int | ID of the current block |
function_code* | String | Function code for the current block |
model_name* | String | Name of the pre-trained model to be used for evaluation |
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