What the function should represent how to shift Θ exactly in the direction of decreasing L how to achieve convergence of the model that is an increase in the quality of its work to a sufficient level how avoid retraining – a situation where the model has learn by heart the training sample and gives unpredictable results on unfamiliar values etc. One of the most widely usd classes of models of the type describe above are the famous artificial neural networks. We will talk about them later. Note for the most meticulous. Often the nature of the pattern we want to model is actually probabilistic. That is the dependence of is not formulate as an object with properties x belongs to class y but an object with properties x usually belongs to class y or even an object with properties x is often belongs to class.
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In this case the problem looks like this: we have a sample from a joint distribution PXYunknown to us. We ned to build the most accurate approximation to the conditional distribution Pyxis possible. In this case our model does not determine the class of the object by its features but something similar to the values of the probabilities of the object Bahrain Email List belonging to each of the classes. But in practice oddly enough from the point of view of implementation these cases are indistinguishable. Let us return however to our individual proposals. The questions Does this particular client need this particular product.
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Is this client ready to open a deposit today? can be consider as classification problems with two classes – positive and negative. With a fairly large historical record of customer reactions to bank offers we can train BTC Email List computer models to answer these kinds of questions. However there is one problem here – in order to accumulate data it will be necessary to send offers at random for a sufficiently long period. And now let’s digress for a while and consider two classes of machine learning problems that are not relate to target sentences – after all the scope of artificial intelligence is not limitd to a single problem.