# CSE-ShU-Advanced-PR-2016 — Data

来源：https://www.kaggle.com/competitions/cse-shu-advanced-pr-2016/data

采集时间：2026-10-24T05:19:05Z

The Galaxy Zoo Decision Tree
Galaxy Zoo guides people through a nested decision tree.
The decision tree consists of 11 questions, with each question having 2-7 responses.
List of Questions
Q1. Is the object a smooth galaxy, a galaxy with features/disk or a star? 3 responses
Q2. Is it edge-on? 2 responses
Q3. Is there a bar? 2 responses
Q4. Is there a spiral pattern? 2 responses
Q5. How prominent is the central bulge? 4 responses
Q6. Is there anything "odd" about the galaxy? 2 responses
Q7. How round is the smooth galaxy? 3 responses
Q8. What is the odd feature? 7 responses
Q9. How tightly wound are the spiral arms? 3 responses
Q10. What shape is the bulge in the edge-on galaxy? 3 responses
Q11. How many spiral arms are there? 6 responses
Paths and the decision tree
Each galaxy's classification is the result of a specific path down a decision tree.  These multiple paths generate probabilities for each node. Volunteers begin with general questions (eg, is it smooth?) and move on to more specific ones (eg, how many spiral arms are there?).
As a result, at each node or question, the total initial probability of a classification will sum to 1.0. Those initial probabilities are then weighted as follows.
Weighting the responses
The values of the morphology categories in the solution file are computed as follows. For the first set of responses (smooth, features/disk, star/artifact), the values in each category are simply the likelihood of the galaxy falling in each category. These values sum to 1.0. For each subsequent question, the probabilities are first computed (these will sum to 1.0) and then multiplied by the value which led to that new set of responses.
Here is a simplified example: a galaxy had 80% of users identify it as smooth, 15% as having features/disk, and 5% as a star/artifact.
Class1.1 = 0.80
Class1.2 = 0.15
Class1.3 = 0.05
For the 80% of users that identified the galaxy as "smooth", they also recorded responses for the galaxy's relative roundness. These votes were for 50% completely round, 25% in-between, and 25% cigar-shaped. The values in the solution file are thus:
Class 7.1 = 0.80 * 0.50 = 0.40
Class 7.2 = 0.80 * 0.25 = 0.20
Class 7.3 = 0.80 * 0.25 = 0.20
This method of cumulatively multiplying probabilities applies for every morphology class, as mapped by the figure above. The sum of Class 1.1-1.3 each galaxy will always sum to 1.0, since this questions are answered for every galaxy. Class 6.1 and 6.2 have also been normalized to sum to 1.0, removing the effect of choosing 1.3 (star/artifact). For the remaining classes, the responses will always sum to <= 1.0.
The reason for this weighting is to emphasize that a good solution must at a minimum get the high-level, large-scale morphology categories correct. The best solutions, though, will also have high levels of accuracy on the detailed solutions that are further down the decision tree.
Tables and Figures
Table 1 explains the decision tree in words.
![](https://storage.googleapis.com/kaggle-media/competitions/inclass/5255/media/Screen-Shot15.jpg)
Figure 1 shows the decision tree.
![](https://storage.googleapis.com/kaggle-media/competitions/inclass/5255/media/Screen%20Shot%202013-09-25%20at%2010.08.17.png)
File descriptions
Images_Train.rar
- the training set
Images_Test.rar
- the test set
Train_Solution.csv -
Training Labels
Sample_Solution.csv
- a sample submission file in the correct format with zero values
.