Home>IT Tests>Questions>Principal component analysis aims at reducing the number of dimensions (or features) in a given data set. The aim is to lower this number to a manageable size but also to preserve the dataset’s integrity structure, trends, categories (and so on) are kept.
Question from the Machine learning - Fundamentals test
Principal component analysis aims at reducing the number of dimensions (or features) in a given data set. The aim is to lower this number to a manageable size but also to preserve the dataset’s integrity structure, trends, categories (and so on) are kept.
Medium
_______ aims at reducing the number of dimensions (or features) in a given data set. The aim is to lower this number to a manageable size but also to preserve the dataset’s integrity structure, trends, categories (and so on) are kept. What is the missing word?
Author: MartinStatus: PublishedQuestion passed 67 times
Edit
0
Community EvaluationsNo one has reviewed this question yet, be the first!
Similar QuestionsMore questions about Machine Learning
11
How to handle missing data in a given training data set ?7
How to handle missing data in a given training data set ?6
The validation set is used to provide frequent and unbiased evaluations of the model’s fit on the training set while tuning its hyperparameters/parameters: in other words,the model is found and then tested on the validation set before to be improved once again.6
What is the missing word in the following sentence: Overfitting is the production of a model that corresponds too closely to the training data set and may therefore fail to fit other data sets and so fail to perform any reliable forecast.4
Clustering is an unsupervised machine learning process which aims at automatically discovering natural grouping in the input data. When using this method, the developer is able to choose the number of groups he wants to create.