# Types of Decision Models - Group 4 - 2018/2019, Semester B, Quartile 3

(Difference between revisions)
 Revision as of 13:35, 17 March 2019 (view source) (→Introduction)← Older edit Revision as of 13:37, 17 March 2019 (view source) (→Nearest Neighbour Strategy)Newer edit → Line 27: Line 27: = Nearest Neighbour Strategy = = Nearest Neighbour Strategy = - NearestNeighbour, short NN, is a mathematical decision model. It is a machine learning decision model, in the sense that existing solutions, often denoted as training data, are used for NN to be able to accurately make predictions about new data such as a user which wants a solution for their airport. This decision model can make the choice which solution fits best to the user. Nearest Neighbour is based on the machine learning strategy KNearestNeighbors [https://brilliant.org/wiki/k-nearest-neighbors/ "Brilliant.org"], Retrieved 17 March 2019. + NearestNeighbour, short NN, is a mathematical decision model. It is a machine learning decision model, in the sense that existing solutions, often denoted as training data, are used for NN to be able to accurately make predictions about new data such as a user which wants a solution for their airport. This decision model can make the choice which solution fits best to the user. Nearest Neighbour is based on the machine learning strategy KNearestNeighbors [https://brilliant.org/wiki/k-nearest-neighbors/ "Brilliant.org: K-nearest Neighbors"], Retrieved 17 March 2019. == Picking variables / attributes == == Picking variables / attributes ==

# Introduction

In this section, we will investigate some different approaches for decision models. These decision models were investigated, but were chosen not to be the final decision model that we will implement. However, for the sake of completeness of this wiki, we will describe our findings on other decision models in this section.

# Nearest Neighbour Strategy

NearestNeighbour, short NN, is a mathematical decision model. It is a machine learning decision model, in the sense that existing solutions, often denoted as training data, are used for NN to be able to accurately make predictions about new data such as a user which wants a solution for their airport. This decision model can make the choice which solution fits best to the user. Nearest Neighbour is based on the machine learning strategy KNearestNeighbors .

## Picking variables / attributes

In order for Nearest Neighbour to work

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# References

1. "Brilliant.org: K-nearest Neighbors", Retrieved 17 March 2019