👉 A classifier is a type of machine learning model that takes in data and outputs a label or category. It is used for tasks such as classification, regression, clustering, and more. The output from the classifier is typically one of two types: either a probability distribution over possible categories (a binary classification) or a numerical value (a continuous classification).
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What is the definition of Classifiers? 🙋
👉 A classifier is a type of machine learning model that takes in input data (often images or text) and outputs an output label. It can be used to classify new data into one of several categories, such as positive or negative. Classifier models are typically trained on labeled data, meaning the training process involves feeding the model examples from the dataset into it and observing how well they classify those examples. This allows the model to learn patterns in the input data that are relevant for making predictions about the output label
