# Exploring Graphs

On the Graphs page, the search results are displayed by a result table, which is a little different from the one in the Results page. This table describes the same results, but these results are served using some statistical measures which are calculated over all trials of searching. The Graphs page is only supported for the manual mode Manual mode is a grid-search mode in the Cognex Deep Learning Parameter Search utility, which runs tests on every selected parameter and their value ranges..

If the Trial in Search page was set to more than 1, the columns will display the minimum, maximum, mean, standard deviation, median, median absolute deviation of the chosen metric at the Metric drop-down list over all trials, given these values of parameters. For example, let us assume the following search configuration is given:

- Tool: Legacy type Red Analyze

- Parameter Set: Luminance, Scale, Epoch Count

- Parameter Range

  - Luminance: 0%, 10%

  - Scale: 0%, 10%

  - Epoch Count: 25, 50

- Trial: 3

If the Luminance, Scale, Epoch Count values at the first row of the result table are {Luminance: 0%, Scale 0%, Epoch Count: 25} and if you set the performance metric as F-Score of Confusion Matrix at the Metric drop-down list, the result table will display the minimum, maximum, mean, standard deviation, median, median absolute deviation of F-Score of Confusion Matrix over 3 trials when Luminance is 0%, Scale is 0%, and Epoch Count is 25, at its first low. See Confusion Matrix of Red Analyze for the details of F-Score of Confusion Matrix.

Note: Before you click Home to go back to Home screen, click Save to save the current parameter search results and graphs. Going back to Home screen will reset all the results and graphs.

In addition to this, 2D contour plots that describe 3 or more variables (dimensions) and depict the search results are given. Especially, these graphs illustrate the relationships between the chosen parameters in terms of the statistical search results over all trials.

To plot the search results on the graph, you first set the x-axis and y-axis of the graph from the parameters used in the search. Set the desired parameters as x-axis and y axis, respectively, using the drop-down lists for each parameter.

Once the 2 axes are set, you are ready to see how the value of a performance metric variates by the values of 2 axes. The numeric values plotted on the graph are basically the values of each performance metric turning up as you scroll through the Metric drop-down list. Plus, in Measure drop-down list, you need to select a statistical measure which is calculated over all trials for the selected metric. The list of the supported measures in the Measure drop-down list is as follows:

- Mean: the mean of the metric over all search trials

- STD: the standard deviation of the metric over all search trials

- MAD: the median absolute deviation of the metric over all search trials

- Median: the median of the metric over all search trials

Choose MAD as the Statistical Measure

For example, if you set Luminance as x-axis, set Scale as y-axis, select F-Score in Metric, and select MAD in Measure, the MAD values of F-Score over all trials will be plotted on the graph following the changes of Luminance (x-axis) and Scale (y-axis) values.

If there are 3 or more parameters, the parameters for x-axis and y-axis can be swapped over among them. The values of parameters other than x-axis and y-axis can also be projected on the graph by selecting the specific values for each parameter's drop-down list.

Note: The Metric drop-down list displays different elements depending on the tool.

### Exploration Workflow

1. Select F-Score in the Metric drop-down list, and this will show the result table for F-Score just below. The columns display the values of parameters and the mean, standard deviation, median, median absolute deviation, minimum, and maximum of F-Score over all trials, given these values of parameters.

   - For Red Analyze tools if you chose Confusion Matrix metrics in Metric drop-down list, Count drop-down (Views, Untrained Views, Regions, Untrained Regions) can be applied to project the graph by each aspect.

   - For Blue tools if you chose Precision, Recall, and F-Score in Metric drop-down list, Count drop-down (Features, Model) can be applied to project the Precision, Recall, F-Score for Features or the Precision, Recall, F-Score for Models on the graph.

2. Provide a measure (mean, standard deviation, median, or median absolute deviation) at the Measure drop-down list, and set the parameters for the x-axis and y-axis.

   - If you previously set more than 1 trial at Trials bar on Search page, there will be many columns where correspond to the F-Scores of each trial (Trial 1, Trial 2, Trial 3, ... , Trial N). The chosen measure for a metric is calculated over all trials.
   - Note that when it was tested with only 1 Trial, the results will not be returned for STD, MAD, Min or Max.

3. Set the values for the parameters other than x-axis and y-axis at each drop-down list. Then, the corresponding contour plot will show up.

4. If you have finished investigating the result table and the graphs, and found the one best set of parameter values, you can go back to the Results page, select a row that describes the best set found in the result table, and click Apply To Workspace to apply the selected set and the trained tool (neural network model Each VisionPro Deep Learning tool is a neural network. A neural network mimics the way biological neurans work in the human brain. The neural network consists of interconnected layers of artifical neurons, called nodes, and they have multiple layers. Neural networks excel at tasks like image classification and pattern recognition.) in the loaded workspace. The tool parameter values and the tool itself in the currently loaded workspace will be replaced with those in the selected row in the result table.