supervised learning वाक्य
उदाहरण वाक्य
मोबाइल
- "Self-training " is a wrapper method for semi-supervised learning.
- In supervised learning models, there are tests that are needed to pass to reduce mistakes.
- The software implements any number of layers of non-linear processing units for supervised learning.
- Hence, a supervised learning algorithm can be constructed by applying an optimization algorithm to find g.
- Support vector machines ( SVMs ) are a set of related supervised learning methods used for regression.
- Description : The first application of supervised learning to gene expression data, in particular Support Vector Machines.
- And some researchers recently proposed Graph-based semi-supervised learning model for language specific NER tasks.
- When labels are more expensive to gather than input examples, semi-supervised learning can be useful.
- In empirical risk minimization, the supervised learning algorithm seeks the function g that minimizes R ( g ).
- Semi-supervised learning is also of theoretical interest in machine learning and as a model for human learning.
- Complementary work that appeared roughly simultaneously showed that quantum annealing can be used for supervised learning in classification tasks.
- For some types of probability models, naive Bayes classifiers can be trained very efficiently in a supervised learning setting.
- Virtually any supervised learning algorithm could be used, such as decision trees, Naive Bayes, and rule induction.
- Interest in supervised learning applications, and even unsupervised learning have since broadened the use and definition of this term.
- Later supervised learning usually works much better when the raw input data is first translated into such a factorial code.
- An ensemble is itself a supervised learning algorithm, because it can be trained and then used to make predictions.
- Explaining their method, the researchers outline their two approaches : " supervised learning " and " community awareness ".
- For supervised learning, there are many other algorithms that use different methods to learn the form of the kernel.
- "' Supervised learning "'is the machine learning task of inferring a function from labeled training data.
- This method for distinguishing plant species is highly efficient since it uses a low resolution 3D Lidar sensor and supervised learning.
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