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chl
chl
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I have a dataset of ~100around 100 different subjects

Some of them have a disease, some do not (roughly 60:40 disease:no disease)

They are subjected to a battery of 15 tests, to see if they are outside "normal" ranges.

Just plotting the values for the different tests for disease vs. non-disease as different colours (using matplotmatplot() in R), I can see that the different groups followingfollow distinct patterns across the different features.

I then cluster the different groups (using hclusthclust() in R) and if I cut the tree to make two clusters, the two groups separate fairly well into different clusters.

My aim is to devise a set of rules from these tests, so if we test a new patient, we can decide whether or not they have a disease.

So I need a classifier, to decide these rules, i.e. to work out which features to use, and what score cutoffs. What do people recommend?

Many thanks.

I have a dataset of ~100 different subjects

Some of them have a disease, some do not (roughly 60:40 disease:no disease)

They are subjected to a battery of 15 tests, to see if they are outside "normal" ranges.

Just plotting the values for the different tests for disease vs. non-disease as different colours (using matplot in R), I see the different groups following distinct patterns across the different features.

I then cluster the different groups (using hclust in R) and if I cut the tree to make two clusters, the two groups separate fairly well into different clusters.

My aim is to devise a set of rules from these tests, so if we test a new patient, we can decide whether or not they have a disease.

So I need a classifier, to decide these rules, i.e. to work out which features to use, and what score cutoffs. What do people recommend?

Many thanks.

I have a dataset of around 100 different subjects

Some of them have a disease, some do not (roughly 60:40 disease:no disease)

They are subjected to a battery of 15 tests, to see if they are outside "normal" ranges.

Just plotting the values for the different tests for disease vs. non-disease as different colours (using matplot() in R), I can see that the different groups follow distinct patterns across the different features.

I then cluster the different groups (using hclust() in R) and if I cut the tree to make two clusters, the two groups separate fairly well into different clusters.

My aim is to devise a set of rules from these tests, so if we test a new patient, we can decide whether or not they have a disease.

So I need a classifier, to decide these rules, i.e. to work out which features to use, and what score cutoffs. What do people recommend?

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Jim Bo
Jim Bo
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Feature selection for disease classification based on tests

I have a dataset of ~100 different subjects

Some of them have a disease, some do not (roughly 60:40 disease:no disease)

They are subjected to a battery of 15 tests, to see if they are outside "normal" ranges.

Just plotting the values for the different tests for disease vs. non-disease as different colours (using matplot in R), I see the different groups following distinct patterns across the different features.

I then cluster the different groups (using hclust in R) and if I cut the tree to make two clusters, the two groups separate fairly well into different clusters.

My aim is to devise a set of rules from these tests, so if we test a new patient, we can decide whether or not they have a disease.

So I need a classifier, to decide these rules, i.e. to work out which features to use, and what score cutoffs. What do people recommend?

Many thanks.