* Add Data * @param {object} xInputObj, {key: value}, key must be the name of the property value must be a String, Number, or Array * @param {*}

* add layer to the model * if the model has 2 or more layers switch the isLayered flag * @param {*} _layerOptions

* creates a barchart from 1 input label and 1 output label * @param {*} inputLabel * @param {*} outputLabel * @param {*} data

* classify is the same as .predict() * @param {*} _inputs

* Classify an new input. It returns an object with a top classIndex and label, confidences mapping all class indices to their confidence, and confiden

* classifyMultiple * @param {*} _input * @param {*} _cb

* classify is the same as .predict() * @param {*} _inputs

* Compile the model * if the model is compiled, set the isCompiled flag to true * @param {*} _modelOptions

* Create an SoundClassifier. * @param {modelNameOrUrl} modelNameOrUrl - The name or the URL of the model to use. Current name options * are:

* Create UNET class. * @param {HTMLVideoElement | HTMLImageElement} video - The video or image to be used for segmentation. * @param {Object} o

* Create a CharRNN. * @param {String} modelPath - The path to the trained charRNN model. * @param {function} callback - Optional. A callback to

* Create Sentiment model. Currently the supported model name is 'moviereviews'. ml5 may support different models in the future. * @param {String} m

* @param {string} urlPath - the directory URL

* @param {HTMLVideoElement | p5.Video | null | undefined} [video] - Can pass a video * into the constructor of the model in order to run the model

* @param {string} urlPath

* Create FaceApi. * @param {HTMLVideoElement} video - An HTMLVideoElement. * @param {object} options - An object with options. * @param {func

* Create Handpose. * @param {HTMLVideoElement} [video] - An HTMLVideoElement. * @param {object} [options] - An object with options. * @param

* Create SketchRNN. * @param {String} model - The name of the sketch model to be loaded. * The names can be found in the models.js file *

* Create a PoseNet model. * @param {HTMLVideoElement || p5.Video} video - Optional. A HTML video element or a p5 video element. * @param {optio

* Create a Pix2pix model. * @param {model} model - The path for a valid model. * @param {function} callback - Optional. A function to run once

* Create an ImageClassifier. * @param {string} modelNameOrUrl - The name or the URL of the model to use. Current model name options * are: 'm

* Create a pitchDetection. * @param {Object} model - The path to the trained model. Only CREPE is available for now. Case insensitive. * @param

* Create a CartoonGan model. * @param {String} modelIdentifier - Required. The name of pre-inluded model or the url path to your model. * @p

* Create Facemesh. * @param {HTMLVideoElement} [video] - An HTMLVideoElement. * @param {object} [options] - An object with options. * @param

* Create BodyPix. * @param {HTMLVideoElement} video - An HTMLVideoElement. * @param {{ * multiplier: Number; * outputStride: Num

* Create ObjectDetector model. Works on video and images. * @param {string} modelNameOrUrl - The name or the URL of the model to use. Current model

* Create YOLO model. Works on video and images. * @param {HTMLVideoElement|HTMLImageElement|HTMLCanvasElement|ImageData} video - Optional. The vid

* Create CocoSsd model. Works on video and images. * @param {function} constructorCallback - Optional. A callback function that is called once the

* Create a new Style Transfer Instance。 * @param {model} model - The path to Style Transfer model. * @param {HTMLVideoElement || p5.Video} video

* Create a KNNClassifier instance.

* Create an DCGAN. * @param {modelName} modelName - The name of the model to use. * @param {function} readyCb - A callback to be called when

* Create a K-Means. * @param {String || array || object} dataset - The dataset to cluster. * @param {options} options - An object describing a m

* Create a DBSCAN. * @param {String || array || object} dataset - The dataset to cluster. in x, y format => [{x:1,y:2}] * @param {options} optio

* Create a Conditional Variational Autoencoder (CVAE). * @param {String} modelPath - Required. The url path to your model. * @param {function} c

* create a new neural network with crossover * @param {*} other

* Delete a project