Tag: introduction
Boosting is an ensemble technique that attempts to create a strong classifier from a number of weak classifiers. This is done by building a model from the training data, …
A downside of K-Nearest Neighbors is that you need to hang on to your entire training dataset. The Learning Vector Quantization algorithm (or LVQ for short) is an artificial …
linear regression is perhaps one of the most well known and well understood algorithms in statistics and machine learning. Isn’t it a technique from statistics? Predictive modeling is primarily …
In , the basic 0/1 knapsack is discussed. For each item, you can choose to put or not to put into the knapsack. Therefore, for the number of items, …
In reality, many applications can be represented as Knapsack problems. The knapsack problem is one of the most classic combinatics mathematics problems. The knapscak problems are of serveral types. …