similarity

问题 I have the following input- query = 'Total replenishment lead time (in workdays)' choices = ['PLANNING_TIME_FENCE_CODE', 'BUILD_IN_WIP_FLAG','Lead_time_planning', 'Total replenishment lead time 1', 'Total replenishment lead time 2'] print(process.extract(query, choices)) I get the following output- [('Total replenishment lead time 1', 92), ('Total replenishment lead time 2', 92), ('Lead_time_planning', 50), ('PLANNING_TIME_FENCE_CODE', 36), ('BUILD_IN_WIP_FLAG', 26)] But I just want all the

问题 I was wondering how is it possible to detect new peaks within an FFT plot in Python. let's say i have this simple Plot: And i want to automatically measure the 'Similarity' or the Peaks location within a noisy Signal, i have tried to use the cosine Similarity but my real Signal is way too noisy, and with even if i add a new peak to the signal, i keep getting a Cosine of 0.9 since it's only one peak. This is an example of my real signal, and i also have the problem that my signal can be

问题 I was wondering how is it possible to detect new peaks within an FFT plot in Python. let's say i have this simple Plot: And i want to automatically measure the 'Similarity' or the Peaks location within a noisy Signal, i have tried to use the cosine Similarity but my real Signal is way too noisy, and with even if i add a new peak to the signal, i keep getting a Cosine of 0.9 since it's only one peak. This is an example of my real signal, and i also have the problem that my signal can be

问题 I have 100 matrices in which each row corresponds to an individual and column refers to sites. I want to sort the row by a measure of similarity such that the most similar individuals are next to each other in a matrix. I used k-nearest neighbours to sort the matrices by rows and I give these sorted matrices to a convolutional neural network. I want to know if there are other measures by which I can achieve the task in hand. The code I use for k-nearest neighbour is: def sort_min_diff(amat):

问题 I have 100 matrices in which each row corresponds to an individual and column refers to sites. I want to sort the row by a measure of similarity such that the most similar individuals are next to each other in a matrix. I used k-nearest neighbours to sort the matrices by rows and I give these sorted matrices to a convolutional neural network. I want to know if there are other measures by which I can achieve the task in hand. The code I use for k-nearest neighbour is: def sort_min_diff(amat):

问题 I have 100 matrices in which each row corresponds to an individual and column refers to sites. I want to sort the row by a measure of similarity such that the most similar individuals are next to each other in a matrix. I used k-nearest neighbours to sort the matrices by rows and I give these sorted matrices to a convolutional neural network. I want to know if there are other measures by which I can achieve the task in hand. The code I use for k-nearest neighbour is: def sort_min_diff(amat):

来源： https://stackoverflow.com/questions/31046269/lucene-scoring-precision-about-vector-space-model

来源： https://stackoverflow.com/questions/31046269/lucene-scoring-precision-about-vector-space-model

问题 I want to be able to find similarity between two strings, weighting each token (word) with its inverse document frequency (those frequencies are not taken from those strings). Using quanteda I can create a dfm_tfidf with inverted frequency weights, but do not know how to proceed after that. Sample data : ss = c( "ibm madrid limited research", "madrid limited research", "limited research", "research" ) counts = list(ibm = 1, madrid = 2, limited = 3, research = 4) cor = corpus(long_list_of

问题 Lets say I have 9 rows of records. Each 3 rows have the same value. For instance: Mike Mike Mike John John John Ryan Ryan Ryan Is there a way I can search for similarities of these records? For example spelling mistakes, additional characters, missing characters, etc. So, for example, the correct version is Mike , but there might be a record down in the list with value Mke which is incorrect (spelling mistake). How can I find this and replace it with the correct one? The above example is