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Supervised Learning and Discriminative Modelling
Supervised Learning is a type of Machine Learning where we teach models using examples that have labels. It
uses labelled datasets to train algorithms to predict outcomes and recognise patterns.
These labels tell the model the correct answer for each example. Discriminative Modelling is a special kind of
supervised learning that focuses on learning how to distinguish different classes. It looks at the features of the
data to figure out which class it belongs to.
Supervised Learning
Supervised learning is a machine learning where a model is trained on a labelled dataset, implying that each
input data point is associated with a corresponding output label. The goal of supervised learning is to learn the
mapping between input data and output labels, enabling the model to make predictions on new, unseen data.
Supervised learning is when we train the machine using labelled data. The machine is provided with a new set
of labelled data so that the supervised learning algorithm analyses the training data and generates the most
suitable and related outcome from the trained-labelled data. Labeled data contains data with the correct output
or classification. In simple words, input data is paired with the desired output thus making the machine learn to
predict the output for new input data.
For example, in the given images, first is the input image and characteristics of this image are marked as boy
and ball, which can be seen in center image. Now, according to supervised learning it has to learn the mapping
between input labels and output labels, which is shown in last image and highlights "ball" as red, "boy" as purple
and "boy playing with a ball" in a rectangle.
Output
Input Features of given image
Label for the item
Boy Ball Boy playing with a ball
In a supervised learning model, a labelled dataset is given to the machine. A labelled dataset is the information
which is tagged with identifiers of data. For example, clothes in a store are marked under various categories of
clothing like Shirts, Trousers, Coats, etc. They are further labelled as per gender and size.
Discriminative Modelling
Discriminative modelling is an approach in machine learning where the focus is on learning the boundary or
decision boundary that separates different classes or categories directly from the data. So, if an image contains
a combination of Dogs and Cats, the model is able to tell which is a Dog and which is a Cat.
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