Analyze some Data using weka in data mining
Project details
Given following datasets in the attachment
1) Training
2) Test
By using the classification algorithms (mentioned below) in weka tool:
1) Train the algorithm using the data given in the training data set file.
2) Classify the data given in the test data set file.
Algorithms to use:
1) ID3
2) KNN
3) Backpropagation
For KNN change the k values and analyze the results that you obtained.
Similarly, for the backpropagation algorithm change the number hidden layers and analyze the results that you obtained.
If you want, you can change other parameters also.
What to submit: Confusion matrices that you obtained for the 3 algorithms and the analysis of the results.
Please submit your results in a pdf or word document.
Awarded to:
Yuriy S.
(5.0)
Project budget: $20 USD
budget limits: $10-30 USD
number of bids: 10
average bids: $67
Awarded to:
Yuriy S.
(5.0)
Project budget: $20 USD
budget limits: $10-30 USD
number of bids: 10
average bids: $67
Project details
Given following datasets in the attachment
1) Training
2) Test
By using the classification algorithms (mentioned below) in weka tool:
1) Train the algorithm using the data given in the training data set file.
2) Classify the data given in the test data set file.
Algorithms to use:
1) ID3
2) KNN
3) Backpropagation
For KNN change the k values and analyze the results that you obtained.
Similarly, for the backpropagation algorithm change the number hidden layers and analyze the results that you obtained.
If you want, you can change other parameters also.
What to submit: Confusion matrices that you obtained for the 3 algorithms and the analysis of the results.
Please submit your results in a pdf or word document.
1) Training
2) Test
By using the classification algorithms (mentioned below) in weka tool:
1) Train the algorithm using the data given in the training data set file.
2) Classify the data given in the test data set file.
Algorithms to use:
1) ID3
2) KNN
3) Backpropagation
For KNN change the k values and analyze the results that you obtained.
Similarly, for the backpropagation algorithm change the number hidden layers and analyze the results that you obtained.
If you want, you can change other parameters also.
What to submit: Confusion matrices that you obtained for the 3 algorithms and the analysis of the results.
Please submit your results in a pdf or word document.
Skills: Data MiningData Processing
skills of Yuriy S.
| skill ? | level ? | projects ? | ||
|---|---|---|---|---|
| Data Mining |
|
3 | ||
| Data Processing |
|
3 | ||
| Data Analysis |
|
1 | ||
| Data Analytics |
|
1 | ||
| Data Science |
|
1 | ||
| Data Visualization |
|
1 | ||
| Data Warehousing |
|
1 | ||
Some Yuriy S. projects
| Project Title | Skills required in the project |
|---|---|
| Analyze some Data using weka in data mining | Data Mining Data Processing |
| Analyze some Data using weka in data mining | Data Mining Data Processing |
