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Data Mining (+ Cleaning): Small Dataset, PCA/Clustering with Python

I need some data cleaning & mining work done. I have a solution in mind, but don't have time to do it properly.

I have a small dataset of attributes for some items.

Some items have common themes - so first I need help grouping those. This can be manually done, probably in 30 mins. (e.g. Item 1 = "Spa", Item 2 = "Spa Facilities" - common theme is "Spa")

Next, I need you to mine the data to identify groups (clusters) of items based on what attributes they have in common. I envision turning those common themes into one-hot vectors, running a PCA on them, then feeding that into a Kmeans algorithm. It's ok to use Scikit-learn, this is just a prototype.

The output has to be the (1) initial dataset with common themes as a new column, and cluster labels added as the last column, (2) code to replicate the work (so I could analyse further).

技能: Data Cleansing, 数据挖掘, 机器学习, Python, 研究

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项目ID: #18135305

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