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Question is simple, how do you read those graphs? I read their explanation and it doesn't make sense to me.
I was reading TensorFlow's newly updated readme file for TensorBoard and in it it tries to explain what a "histogram" is. First it clarifies that its not really a histogram:
Right now, its name is a bit of a misnomer, as it doesn't show histograms; instead, it shows some high-level statistics on a distribution.
I am trying to figure out what their description is actually trying to say.
Right now I am trying to parse the specific sentence:
Each line on the chart represents a percentile in the distribution over the data: for example, the bottom line shows how the minimum value has changed over time, and the line in the middle shows how the median has changed.
The first question I have is, what do they mean by "each line". There are horizontal axis and there are lines that make a square grid on the graph or maybe the plotted lines, themselves. Consider a screen shot from the TensorBoard example:
What are they referring to with "lines"? In the above example what are the lines and percentiles that they are talking about?
Then the readme file tries to provide more detail with an example:
Reading from top to bottom, the lines have the following meaning: [maximum, 93%, 84%, 69%, 50%, 31%, 16%, 7%, minimum]
However, its unclear to me what they are talking about. What is lines and what percentiles?
It seems that they are trying to replace this in the future, but meanwhile, I am stuck with this. Can someone help me understand how to use this?
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Simply speaking, if the possible values are in a range of 0.. 9 and you see a spike of amount 10 on the value 0 , this means that 10 inputs assume the value 0 ; in contrast, if the histogram shows a plateau of 1 for all values of 0.. 9 , it means that for 10 inputs, each possible value 0.. 9 occurs exactly once.
Tensorboard works by reading the event files which is where Tensorflow writes the summary data (the data to be visualized). It usually comes installed with Tensorflow and to execute it simply run the following command: tensorboard --logdir=[dir] where [dir] is the event files location.
TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. It enables tracking experiment metrics like loss and accuracy, visualizing the model graph, projecting embeddings to a lower dimensional space, and much more.
Distributions displays the distribution of each non-scalar TensorFlow variable across iterations. These variables are the free parameters of your model and approximating family.
The lines that they are talking about are described below:
as for the meaning of percentile, check out the wikipedia article, basically, the 93rd percentile means that 93% of the values are situated below the 93rd percentile line
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