https://github.com/tentone/semeionnet
A set of machine learning experiments with the semeion and MNIST handwritten digit dataset using tensorflow
https://github.com/tentone/semeionnet
mnist semeion tensorflow
Last synced: 9 months ago
JSON representation
A set of machine learning experiments with the semeion and MNIST handwritten digit dataset using tensorflow
- Host: GitHub
- URL: https://github.com/tentone/semeionnet
- Owner: tentone
- License: mit
- Created: 2017-10-12T21:05:35.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2020-03-15T17:01:19.000Z (almost 6 years ago)
- Last Synced: 2025-03-24T03:12:13.674Z (10 months ago)
- Topics: mnist, semeion, tensorflow
- Language: Python
- Size: 10.9 MB
- Stars: 3
- Watchers: 2
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# SemeionNet
- A set of machine learning experiments with the semeion and MNIST handwritten digit dataset using tensorflow
- The objective of this experiment was to test multiple classification methods using the semeion handwriting dataset and measure performance of different classifiers implementation in tensorflow.
### Dataset
- The semeion dataset is composed of 1593 handwritten digits from 80 persons that were scanned and stretched to a 16x16 size image.
- http://archive.ics.uci.edu/ml/datasets/semeion+handwritten+digit
- MNIST dataset is a subset of the NIST dataset that has over 60000 handwritten digits.
- http://yann.lecun.com/exdb/mnist/
- To change the dataset, change the dataset loading code and sample size in the implementation files.
- If you want to you can also import your own dataset, this code can be easily adapted to classify other type of images.
```
width = 16
height = 16
dataset = semeion.read_data_semeion()
```
### Install
- The code available was tested with Python 3.5 and Tensorflow 1.1
- Before running the examples in the repository, install the dependencies.
```
tensorflow matplotlib sklearn pandas numpy
```
### Build and Run
- Clone the repository into your computer
- https://github.com/tentone/SemeionNet.git
- Dataset files are already included in the repository inside the /source/dataset folder.
- Run one of the implementation files from the source folder, each one implements a diferent classifier.
- knn.py, softmax.py, perceptron.py, cnn.py, lstm.py
### Result Comparison
- The results bellow were obtained, using 1300 random entries from the semeio dataset to train the classifier and 400 random entries to test the trained model.
- The results obtained are expected, for the recurrent network (long short term memory), i haven't applied any confusion to the input, so after some time it detects that probably the next sample its equal to the current one.
- Tests were run on a Core i5 6500 CPU with 24GB of RAM.
| Classifier | Time | Accuracy |
| ----------- | ---- | -------- |
| Softmax | 40.8 | 94.32% |
| KNN | 3.85 | 94.52% |
| Perceptron | 11.4 | 97.16% |
| CNN | 89.7 | 96.95% |
| RNN | 35.1 | 97.56% |