WEKA API several/19: Having Analysis (Division)

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Using WEKA in java

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Digital Signal Processing (DSP) refers to the process whereby real-world phenomena can be translated into digital data for analysis, manipulation, and synthesis. DSP has transformed the way we interact with the physical world when it comes to recording sound, taking pictures, or analyzing other natural phenomena. None of this would be possible without the Fast Fourier Transform (FFT) algorithm, which allows huge amounts of data sampled in the time domain to be quickly transformed into the frequency domain. In this Digital Signal Processing Tutorial, we discuss implementations of the FFT in JavaScript and how we as developers can leverage JavaScript libraries such as DSP.js for signal analysis, synthesis, and manipulation.

Watch this video to learn:

– What is Digital Signal Processing (DSP)
– What is the Fast Fourier Transform (FFT) algorithm
– How does DSP work
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27 Gedanken zu „WEKA API several/19: Having Analysis (Division)“

  1. Make a video on how to get string/nominal attributes from user in java and then make predictions by training the classifier with some train.arff file ?

  2. hi, im trying to predict with a model, i follow all the steps but i continue receiving this error… any idea?

    CLONALG v1.0.
    java.io.IOException: No source has been specified

    at weka.core.converters.ArffLoader.getDataSet(ArffLoader.java:1003)
    at weka.core.converters.ConverterUtils$DataSource.getDataSet(ConverterUtils.java:268)
    at javaapplication2.JavaApplication2.main(JavaApplication2.java:32)
    Exception in thread "main" java.lang.NullPointerException
    at javaapplication2.JavaApplication2.main(JavaApplication2.java:34)

  3. If I want to classify a dataset with unknown class does all the attributes have to be the same as the original training set? For example only words in the training set can be used in the same order?

  4. thank you for the tutorial..

    excuse me sir, can i get the sample code from this video, i click the link in this video description, but i cant found it..

  5. To use the trained model to predict values on new data, the class column was left blank and the evaluation was done. But Weka throws the error "train and test are not compatible". How can this be fixed

  6. How can we predict a single instance in a data set. after training with massive training dataset.
    Eg – train with iris dataset and then prediction need to give when we provice a single instance?

    Thank you

  7. This might sound super naive and silly, but how do I know what filters to use on a signal? Is there a standard finite set that is frequently used in practice?

  8. well i did this with my mind and they told me to tell you from The Challenger to stop or they will flood and send 6 hurricanes and wash u out…that was the message they gave me. ok. moving on. when u MANIPULATE things it throws off the flow. a primitive root they told me… THEY ARE MAAAAD at us with this "technology"… theyve HAD it. oh and they waved to tell u hi, well me hi doesnt matter… they gave me a number, i guess ill use it when its time for me to use it….i got this from "ancient aliens"…lmao

  9. Great talk! I'm starting with DSP because I want to get frequency from 3-axis accelerometer signals to compute respiration rate and I'm using FFT. This video was helpful, thank you.

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