Is factor analysis the same as cluster analysis?

Is factor analysis the same as cluster analysis?

Factor analysis is an exploratory statistical technique to investigate dimensions and the factor structure underlying a set of variables (items) while cluster analysis is an exploratory statistical technique to group observations (people, things, events) into clusters or groups so that the degree of association is …

In what cases do you think K means clustering would fail?

K-Means clustering algorithm fails to give good results when the data contains outliers, the density spread of data points across the data space is different and the data points follow non-convex shapes.

Is factor analysis supervised or unsupervised?

Factor analysis is one of the unsupervised machine learning algorithms which is used for dimensionality reduction.

How is cluster analysis used in factor analysis?

In factor analysis, we take several variables, examine how much variance these variables share, and how much is unique and then ‘cluster’ variables together that share the same variables. In short, we cluster together variables that look as though they explain the same variance.

How are dependent variables used in cluster analysis?

Cluster analysis does not differentiate dependent and independent variables. Cluster analysis is used in a wide variety of fields such as psychology, biology, statistics, data mining, pattern recognition and other social sciences. The main objective is to address the heterogeneity in each set of data.

How are variables grouped according to shared variance?

We have already seen that we can use Factor Analysis to group variables according to shared variance. In factor analysis, we take several variables, examine how much variance these variables share, and how much is unique and then ‘cluster’ variables together that share the same variables.

How are clusters merged in a cluster analysis?

Most of these methods work in a hierarchical way. The principle behind each method is similar in that it begins with all cases being treated as a cluster in its own right. Clusters are then merged based on a criterion specific to the method chosen.