Mean Shift with Titanic Dataset - Practical Machine Learning Tutorial with Python p.40

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We continue the topic of clustering and unsupervised machine learning with Mean Shift, this time applying it to our Titanic dataset.

There is some degree of randomness here, so your results may not be the same. You can probably re-run the program to get similar data if you don't get something similar, however.

We're going to take a look at the Titanic dataset via clustering with Mean Shift. What we're interested to know is whether or not Mean Shift will automatically separate passengers into groups or not. If so, it will be interesting to inspect the groups that are created. The first obvious curiosity will be the survival rates of the groups found, but, then, we will also poke into the attributes of these groups to see if we can understand why the Mean Shift algorithm decided on the specific groups.

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Tags:
mean shift
python
clustering
flat clustering
hierarchical clustering
unsupervised machine learning
machine learning
tutorial
artificial intelligence
scikit-learn
sklearn
tensorflow
theano