BA Quizzes 9 & 10

Which of the following is a disadvantage of neural networks?

All of the above are weaknesses of neural networks.

The choice of k (number of clusters in a Cluster Analysis) can be made using a variety of methods. Which of the following methods is appropriate in selecting the number of clusters

All of the methods listed above are appropriate

The choice of k (number of clusters in a Cluster Analysis) can be made using a variety of methods. Which of the following methods is appropriate in selecting the number of clusters.

All the methods listed above are appropriate

Neural Networks can be used to predict:

Both continuous and categorical dependent variables

The Euclidean distances of a customer from the different cluster centers are given below. Based on this information, which cluster the customer belongs to?

Cluster 4

Which of the following is an un-supervised data mining technique?

Cluster Analysis

Where would you most likely see a dendrogram?

In a hierarchical clustering algorithm

You want to group custommers in your dataset by similarity and assign labels to each group. What is the preferred analytic method to use for this task?

K-means clustering

What are the outputs generated by a k-Means clustering Analysis?

The centroids of the discovered cluster and the assignment of each input datum to a cluster.

Cluster analysis is a very attractive initial data-mining tool because it can be used to discover rules and patterns.

True

A good clustering technique will create low similarity within a cluster and high similarity between the clusters.

false

A required preparatory task in cluster analysis is to transform continuous variables into categorical variable types that can then be input into the model.

false

Cluster Analysis is a supervised learning technique.

false

In an online bookstore, making recommendations to customers concerning additional items to buy based on the buying patterns in prior transactions is an example of cluster Analysis technique.

false

In order to include a categorical variable in k-means cluster analysis in JMP, the data must be coded numerically. Therefore, categorical variables should be coded as 0/1.

false

Which of the following activation functions is not used in neural networks (in JMP)?

none of the above

A good clustering scheme will have little variation within clusters and signficant variation between clusters.

true

According to the text, the most popular choice for the number of hidden layers is one.

true

Cluster analysis is an un-supervised technique.

true

Cluster analysis refers to grouping of records that are similar to one another

true

In Cluster analysis, it is important to normalize the data to get rid of differences in scale.

true

In K-Mean clustering technique, the user has to pick the number of clusters.

true

K-Means clustering is well suited to the task of Market segmentation.

true

K-means algorithm is a typical algorithm for cluster analysis that uses "Euclidean distance" to find clusters.

true

Neural Networks were originally developed to understand biological neural networks.

true

Neural networks can be used for both continuous and categorical dependent (output) variables.

true

One advantage of neural networks is that there is very little chance of overfitting, so validation or testing data is not needed.

true

One disadvantage of neural networks is that they are slow learners.

true

One-way to decide on the number of clusters in a K-means cluster analysis is to arbitrarily pick a value.

true

The "K" in K-Means Cluster Analysis refers to the maximum number of variables that a clustering model can utilize.

true

The curse of dimensionality refers to the computational complexity of developing clusters using a large number of variables.

true

The most popular method for using model errors to update weights is called back propagation of error.

true

Training a neural network model involves estimating the weights that will lead to the best predictive results.

true