Classification | Data classification using Accord.NET framework | Machine Learning library

 by   ClaudiuGeorgiu C# Version: Current License: MIT

kandi X-RAY | Classification Summary

kandi X-RAY | Classification Summary

Classification is a C# library typically used in Artificial Intelligence, Machine Learning applications. Classification has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Data classification using Accord.NET framework. This is a simple C# application developed in Visual Studio (using WinForms GUI) to explore some of the functionalities of the Accord.NET framework regarding data classification. You can import some data in .csv format and compare the performances of different classification algorithms.
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            kandi-support Support

              Classification has a low active ecosystem.
              It has 4 star(s) with 5 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              Classification has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Classification is current.

            kandi-Quality Quality

              Classification has no bugs reported.

            kandi-Security Security

              Classification has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              Classification is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              Classification releases are not available. You will need to build from source code and install.

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            Classification Key Features

            No Key Features are available at this moment for Classification.

            Classification Examples and Code Snippets

            Generate a classification signature definition .
            pythondot img1Lines of Code : 54dot img1License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def classification_signature_def(examples, classes, scores):
              """Creates classification signature from given examples and predictions.
            
              This function produces signatures intended for use with the TensorFlow Serving
              Classify API (tensorflow_servi  
            Initialize the classification output .
            pythondot img2Lines of Code : 30dot img2License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def __init__(self, scores=None, classes=None):
                """Constructor for `ClassificationOutput`.
            
                Args:
                  scores: A float `Tensor` giving scores (sometimes but not always
                      interpretable as probabilities) for each class.  May be `None`,   
            Sort the classification .
            pythondot img3Lines of Code : 29dot img3License : Permissive (MIT License)
            copy iconCopy
            def sort(self, sample: list[float]) -> None:
                    """
                    :param sample: example row to classify as P1 or P2
                    :return: None
                    >>> data = [[2.0149, 0.6192, 10.9263]]
                    >>> targets = [-1]
                    >>&  

            Community Discussions

            QUESTION

            Tidymodels / XGBoost error in last_fit with rsplit value
            Asked 2021-Jun-15 at 04:08

            I am trying to follow this tutorial here - https://juliasilge.com/blog/xgboost-tune-volleyball/

            I am using it on the most recent Tidy Tuesday dataset about great lakes fishing - trying to predict agency based on many other values.

            ALL of the code below works except the final row where I get the following error:

            ...

            ANSWER

            Answered 2021-Jun-15 at 04:08

            If we look at the documentation of last_fit() We see that split must be

            An rsplit object created from `rsample::initial_split().

            You accidentally passed the cross-validation folds object stock_folds into split but you should have passed rsplit object stock_split instead

            Source https://stackoverflow.com/questions/67978723

            QUESTION

            Keras model not compiling
            Asked 2021-Jun-14 at 07:01

            I am trying to build a Keras model for a classification model and I get and error while I am trying to fit the data.

            ValueError: Shapes (None, 99) and (None, 2) are incompatible

            Code:

            ...

            ANSWER

            Answered 2021-Jun-14 at 07:01

            The no. of units in the last Dense layer must match the dimensionality of the outputs.

            Source https://stackoverflow.com/questions/67964504

            QUESTION

            How to get indices of instances during cross-validation
            Asked 2021-Jun-13 at 17:04

            I am doing a binary classification. May I know how to extract the real indexes of the misclassified or classified instances of the training data frame while doing K fold cross-validation? I found no answer to this question here.

            I got the values in folds as described here:

            ...

            ANSWER

            Answered 2021-Jun-13 at 17:04

            From cross_val_predict you already have the predictions. It's a matter of subsetting your data frame where the predictions are not the same as your true label, for example:

            Source https://stackoverflow.com/questions/67956643

            QUESTION

            Pandas: Insert a new Column based on description of previous column
            Asked 2021-Jun-13 at 15:51

            I have a dataset of around 2800 records. I have a column called as 'Trigger-catogory' which is a Multi-class classification field with one of the attribute being 'CLI-Related' The dataset has a 'Headline' column and going through the headline i want to further classify it . I have written a code as below

            ...

            ANSWER

            Answered 2021-Jun-13 at 15:51

            use vectorized way via np.select to insert a new column:

            Source https://stackoverflow.com/questions/67959492

            QUESTION

            Can I use a convolution filter instead of a dense layer for clasification?
            Asked 2021-Jun-13 at 08:50

            I was reading a decent paper S-DCNet and I fell upon a section (page3,table1,classifier) where a convolution layer has been used on the feature map in order to produce a binary classification output as part of an internal process. Since I am a noob and when someone talks to me about classification I automatically make a synapse relating to FCs combined with softmax, I started wondering ... Is this a possible thing to do? Can indeed a convolutional layer be used to classify a binary outcome? The whole concept triggered my imagination so much that I insist on getting answers...

            Honestly, how does this actually work? What is the difference between using a convolution filter instead of a fully connected layer for classification purposes?

            Edit (Uncertain answer on how does it work): I asked a colleague and he told me that using a filter of the same shape as the length-width shape of the feature map at the current stage, may lead to a learnable binary output (considering that you also reduce the #channels of the feature map to a single channel). But I still don't understand the motivations behind such a technique ..

            ...

            ANSWER

            Answered 2021-Jun-13 at 08:43

            Using convolutions as FCs can be done (for example) with filters of spatial size (1,1) and with depth of the same size as the FC input size.

            The resulting feature map would be of the same size as the input feature map, but each pixel would be the output of a "FC" layer whose weights are the weights of the shared 1x1 conv filter.

            This kind of thing is used mainly for semantic segmentation, meaning classification per pixel. U-net is a good example if memory serves.

            Also see this.
            Also note that 1x1 convolutions have other uses as well.
            paperswithcode probably some of the nets there use this trick.

            Source https://stackoverflow.com/questions/67525656

            QUESTION

            Is it possible to combine 2 neural networks?
            Asked 2021-Jun-13 at 00:55

            I have a NET like (exemple from here)

            ...

            ANSWER

            Answered 2021-Jun-07 at 14:26

            The most naive way to do it would be to instantiate both models, sum the two predictions and compute the loss with it. This will backpropagate through both models:

            Source https://stackoverflow.com/questions/67872719

            QUESTION

            How and where can i freeze classifier layer?
            Asked 2021-Jun-12 at 20:29

            If I need to freeze the output layer of this model which is doing the classification as I don't need it.

            ...

            ANSWER

            Answered 2021-Jun-11 at 15:33

            You are confusing a few things here (I think)

            Freezing layers

            You freeze the layer if you don't want them to be trained (and don't want them to be part of the graph also).

            Usually we freeze part of the network creating features, in your case it would be everything up to self.head.

            After that, we usually only train bottleneck (self.head in this case) to fine-tune it for the task at hand.

            In case of your model it would be:

            Source https://stackoverflow.com/questions/67939448

            QUESTION

            Having trouble with XML phase on VBA Excel
            Asked 2021-Jun-12 at 17:26

            I need to parse a XML file having the structure as follows: (I can't show the data as it is confidential)

            ...

            ANSWER

            Answered 2021-Jun-12 at 17:26

            As mentioned in comments your xml document has namespace definitions in its DocumentElement (xmlns stands for xml name space). Furthermore "it contains a default namespace so any attempted parsing on named nodes must map to this namespace URI otherwise returns nothing."

            To allow eventual analysis it's necessary to include a user defined prefix (e.g. :s) into explicit namespace settings, which can be used in later XPath expressions:

            Source https://stackoverflow.com/questions/67949350

            QUESTION

            How can I delete rows if a column contains a certain value?
            Asked 2021-Jun-11 at 16:23

            I have a data frame that has a classification column which contains four values: D1, D2, D8, and RD.

            I want to remove all records (rows) where the classification is either D1 or RD.

            I have tried this:

            ...

            ANSWER

            Answered 2021-Jun-11 at 10:34

            It's better to think "how do I create an object in the form I want", than "how do I manipulate this object in place". So you can use the following syntax:

            Source https://stackoverflow.com/questions/67935426

            QUESTION

            Is there some way to simplify access to the first member of a group in a LINQ GroupBy query?
            Asked 2021-Jun-11 at 15:04

            I have the following LINQ statement that collects the results by the Site:

            ...

            ANSWER

            Answered 2021-Jun-11 at 15:04

            You can do that by additional Select:

            Source https://stackoverflow.com/questions/67920276

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install Classification

            You can download it from GitHub.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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