What is the proportion of deliveries that arrived on time in the given dataset?

Use rpart to build a decision tree based on the dataframe created from the given dataset. Train the model on only the descriptive features, but excluding ID. Set the parameters as follows: complexity parameter should be 0.01, the minimum split size should be 2, the minimum leaf size should be 1, and the maximum tree depth should be 5. How many nodes does the resulting decision tree have?

Consider the SOM shown below which was trained on an RGB data set using a sigma of 10.

To improve the result:

Consider the SOM presented below:

 The bottom left corner represents

When using a self-organizing feature map for data imputation, which of the following approaches will provide a more accurate estimate for a missing value?

Consider the SOM shown below which was trained on an RGB data set using a learning rate of 0.9.  

To improve the results:

SOM training is robust to missing values.

Consider the self-organising map below, which shows the h values calculated using a Gaussian neighbourhood function. Which instance is the best matching unit? Provide your answer in the format x,y, where x represents the row and y represents the column. Do not include any spaces.

                1             2             3

1             1.000    0.607    0.135

2             0.607    0.368    0.082

3             0.135    0.082    0.018

Consider the self-organizing map belo, which shows the h values calculated using a Gaussian neighbourhood function. Are the h values correctly calculated? Assume the learning rate is one and sigma is one.

                1             2             3

1             0.268    0.607    0.268

2             0.607    1.000    0.607

3             0.268    0.607    0.268

Calculate the quantization error for the network below given instances, 2 and 3.

                1             2             3             4            

1             1.2         1.4         2.4         3.0

2             1.4         2.2         2.6         3.2

3             1.8         2.7         2.6         3.4

4             2.0         2.8         2.8         3.5