Hi,
I have a dataset (text) and I don't know the labels of its samples. I want to classify these samples, but I need to first label samples. So it is impossible (and time consuming) to manually label samples. I want to use clustering algorithms to label samples and then use supervised (classification) methods to classify samples. This might be helpful:
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Hi. I can apply KMeans or GMM to your problem, estimate the number of clusters or mixtures K with BIC, AIC information criterions and then do classifications with logreg or any other classifier you like. I am experienced in using Python to work with data and then applying Machine Learning to it. Have worked with text classification.
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I have a good hands on working with Advanced Excel, R and Python. I have quite a good knowledge of deep learning Algorithm , have also developed dashboards and Shiny Web Application in R
I understand the project requirement and will deliver the desired product within the time specified.
Hello,
I can assist you in clustering your data. Clustering aims to group data with no prior knowledge in advance. I don't know if this is the case or not, but perhaps this step could be enough to classify your data.
You can also use Amazon truck for manual labeling else what you suggested would definitely work, I have done a similar project using NLP let me know if I can help you