Mathematics, 18.06.2021 21:20 destany25

How would u define a cluster and an outliner?

Answers: 2

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Everyone is trying to make sense of their data. In the real world, data is often not easy to separate, and patterns are not usually obvious. Clustering helps you find similarity groups in your data and it is one of the most common tasks in the Data Science. Finding the "outliers", which are the observations in your data isolated from the rest of observations, is often a non-easy analytics task by its own. It explains why the density-based clustering, which find similarity groups and outliers in your data simultaniously, is one of the most common clustering algorithms.

You can control the algorithm parameters and the visual attributes to suit your needs.

Here is how it works:

Define the fields to be used in clustering (two or more numerical variables) Optionally, provide the labels to be shown on top of each observation If the dimensionality of data is higher than two, consider data preprocessing DBSCAN algorithm requires 2 parameters to control the granularity of clusters. They can be set manually by user (recommended) or automatically by underlying algorithm When you are sattisfied with clustering output, use numerous formatting controls to refine the visual apperance of the plot

Step-by-step explanation:

Hope this helps! :P

Answer from: lucylooe11

A cluster is defined as a group of information (data points and numbers) that are located close together

An Outlier is a number that does not fit in a graph or a data set, like it could be abnormally big or abnormally small.

Answer from: Quest

its the fourth option

The diagram shows the repairs performed on 2 types of cars. compare the car types using the median a

Answer from: Quest

( - 4 , -7 )

all the lines must parallel

step-by-step explanation:

coordinates of c = ( - 1 , 2 )

3 units left = ( -4 , 2 )

9 units down = ( - 4 , 11 )

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