Skip to main content
Cross Validated

Return to Question

Bumped by Community user
Scoring tag deprecated hence removed
Link
mdewey
mdewey
  • 18.4k
  • 23
  • 35
  • 61
added 134 characters in body; edited title
Source Link
Phil B
Phil B
  • 101
  • 3

Is there a distance scoring algorithm similar to Jaccard distance that handles incomplete / missingscalar data?

we have the characteristics and (scalar) values of those characteristics for three (or more) people:

Person A: {height: 1, weight: 2, type: 1}

Person B: {height: 1, weight: 2, type: 5}

Person C: {weight: 2, type: 1}

I'm trying find a distance measure that helps decide if Person A and C are more similar to each other or if Person A and B are.

If we had categorical data, I would use the Jaccard distance, but now I am trying to include the scalar values in the calculation.

The key concept is that there are some pairings where the characteristic set is incomplete and I would like to know if there is any distance scoring algorithm that handles that elegantly.

PS I'm not really sure how to ask this question and quite new at this, so please feel free to ask me to edit / rephrase rather than closing the question if it's not up to community standards.

Is there a distance scoring algorithm that handles incomplete / missing data?

we have the characteristics and (scalar) values of those characteristics for three (or more) people:

Person A: {height: 1, weight: 2, type: 1}

Person B: {height: 1, weight: 2, type: 5}

Person C: {weight: 2, type: 1}

I'm trying find a distance measure that helps decide if Person A and C are more similar to each other or if Person A and B are.

The key concept is that there are some pairings where the characteristic set is incomplete and I would like to know if there is any distance scoring algorithm that handles that elegantly.

PS I'm not really sure how to ask this question and quite new at this, so please feel free to ask me to edit / rephrase rather than closing the question if it's not up to community standards.

Is there a distance algorithm similar to Jaccard distance that handles scalar data?

we have the characteristics and (scalar) values of those characteristics for three (or more) people:

Person A: {height: 1, weight: 2, type: 1}

Person B: {height: 1, weight: 2, type: 5}

Person C: {weight: 2, type: 1}

I'm trying find a distance measure that helps decide if Person A and C are more similar to each other or if Person A and B are.

If we had categorical data, I would use the Jaccard distance, but now I am trying to include the scalar values in the calculation.

The key concept is that there are some pairings where the characteristic set is incomplete and I would like to know if there is any distance scoring algorithm that handles that elegantly.

PS I'm not really sure how to ask this question and quite new at this, so please feel free to ask me to edit / rephrase rather than closing the question if it's not up to community standards.

Source Link
Phil B
Phil B
  • 101
  • 3

Is there a distance scoring algorithm that handles incomplete / missing data?

we have the characteristics and (scalar) values of those characteristics for three (or more) people:

Person A: {height: 1, weight: 2, type: 1}

Person B: {height: 1, weight: 2, type: 5}

Person C: {weight: 2, type: 1}

I'm trying find a distance measure that helps decide if Person A and C are more similar to each other or if Person A and B are.

The key concept is that there are some pairings where the characteristic set is incomplete and I would like to know if there is any distance scoring algorithm that handles that elegantly.

PS I'm not really sure how to ask this question and quite new at this, so please feel free to ask me to edit / rephrase rather than closing the question if it's not up to community standards.