OriginLab Technical Support

3/25/2020

11/11/2021

231

2

51 KB

SVM Classi...on.opx

1.80

Free

Support vector machine for classification.

**Note**: Scikit-learn library is used for this app, so some related python libraries are needed for this app, such as setuptools, numpy, scipy, scikit-learn, scikit-image, and their dependent libraries. You can use pip to install them first.**Purpose**

This app can be used to perform the support vector machine algorithm for classification.**Features Include:**- Peform support vector machine algorithm and output the related parameters.
- Predict the class labels for specified data.
- Multiple kernels are supported, including linear, poly, rbf, and sigmoid.
- Decision function can be one vs rest or one vs one.
- For 2 Dimensions' X data, territorial map plot is available for output.

**Installation**

Download the file "SVM Classification.opx", and then drag-and-drop onto the Origin workspace. An icon will appear in the Apps gallery window.**Operation**- Import desired data into a worksheet.
- Select X columns for training, and click the icon in the Apps Gallery panel.
- In the pop up dialog, select one column as training Y.
- If you want to make prediction for another dataset, check Predict checkbox, and select the dataset.
- In the Options tab, change the parameters as needed for your case. For details for each parameter, see Dialog Settings below.
- If the training X is 2 dimensions, in the Output tab, you can select to make territorial map plot or not.
- Click OK button to create report.

**Dialog Settings****Input Tab**- Training X: X dataset of the samples.
- Training Y: Y data of the samples.
- Predict: If checked, perform prediction for the specified X dataset.
- X to Predict: Available if Predict is checked, is to specified the X dataset for prediction.

**Options Tab**- Regularization Parameter: The strength of the regularization is inversely proportional to this regularization parameter. Its penalty is squred L2 penalty.
- Kernel: Kernel type for the algorithm, including linear, poly, rbf, and sigmoid.
- Degree: If kernel is poly, this is for specifying the degree of the polynomial kernel function.
- Gamma: This is available when Kernel is poly, rbf or sigmoid. Default is scale.
- Gamma Value: This is the value for specified gamma.
- Independent Term: This is available when Kernel is poly or sigmoid, used to specify the independent term in kernel function.
- Shrinking Heuristic: Whether to use the shrinking heuristic.
- Estimate Probability: Whether to enable probability estimates.
- Tolerance: Tolerance for stopping criterion.
- Max Iterations: Max number of iterations for stopping the solver, and -1 for no limit.
- Decision Function: Specify decision function, one vs rest or one vs one.
- Specify Random State: Check to specify the seed of pseudo random number generator used when shuffling the data for probability estimates.
- Random State: Specify the seed of pseudo random number generator.

**Output Tab**- Territorial Map: Check to output territorial map plot. This is for training X with 2 dimensions.
- X1 Minimum: The minimum value of the first dimension of training X.
- X1 Maximum: The maximum value of the first dimension of training X.
- X2 Minimum: The minimum value of the second dimension of training X.
- X2 Maximum: The maximum value of the second dimension of training X.
- Number of Points for X1: Number of points for the first dimension of training X to make the territorial map plot.
- Number of Points for X2: Number of points for the second dimension of training X to make the territorial map plot.
- Report Table: The report table to output the results.
- Report Data: The worksheet to output the report data.

**OK:**Click this button to create report.**Cancel:**Close dialog without doing anything.

**References**- This app is calling sklearn.svm.SVC for the calculation, please refer to svm classification for more details.

v1.8: Update to using pip command to install related Python libraries

v1.7: Fix bug for categorical data as x

v1.6: Update for Python 3.8

v1.5: Fix bug for colormap of territorial map

v1.4: Update for Origin 2021

v1.3: Support data filter for group (class) column

v1.2: Fixed bug of creating territorial map issue, and auto install dependent Python packages

v1.1: Fixed speed issue of updating plot and issue of dependent Python packages

08/28/2022 | XC1119796177 | It would be better if some teaching vidio regarding SVM can be uploaded. | |

10/27/2020 | venyipaul@yahoo.com | Thank you OriginLab |