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Results tagged with classification
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user 107579
Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a variable behavior which can be studied by statistics.
4
votes
Classification algorithms for handling Imbalanced data sets
I recommend trying an combined method such as SMOTE + Tomek links to see if classification accuracy improves on a balanced dataset.
See ipython notebook for an example. …
- 1,168
0
votes
Convolutional neural network and Transfer Learning
With transfer learning you can re-train the last few layers of your network to learn to classify images on your new dataset. For an example of transfer learning in TensorFlow using VGG16 and Inception …
- 1,168
7
votes
1
answer
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Word embeddings with logistic regression
My goals is to classify a set of documents (e.g. 20newsgroups) into one of twenty categories. I can do this using Logistic Regression for example which takes as input a sparse $D\times V$ matrix in wh …
- 1,168
7
votes
Word embeddings with logistic regression
While it's possible to combine word embeddings using weighted average or a concatenation of min / max values across word vectors as described in this post, the output vector loses semantic information …
- 1,168
1
vote
Can a labeled LDA (Latent Dirichlet Allocation) dataset have just one label per document?
In supervised LDA a single label is added for each document (in addition to topic labels for each word). This label known as response variable reflects some quantity of interest associated with a docu …
- 1,168