query: Better way to normalize this kind of data where samples are very similar to each other?
positive_passages.docid: 146238
positive_passages.text: How to deal with a data-set having all the samples with every feature-point almost similar?
negative_passages.docid: 55847
negative_passages.text: PCA demeaning the data
negative_passages.docid: 33141
negative_passages.text: Subsample of a random sample?
negative_passages.docid: 58792
negative_passages.text: Why would perfectly similar data have 0 mutual information?
negative_passages.docid: 55917
negative_passages.text: Verifying representativeness of a sample, after simple random sampling
negative_passages.docid: 40442
negative_passages.text: Is up- or down-sampling imbalanced data actually that effective? Why?
negative_passages.docid: 6024
negative_passages.text: How to deal with hierarchical / nested data in machine learning
negative_passages.docid: 14465
negative_passages.text: "Normalizing" variables for SVD / PCA
negative_passages.docid: 4337
negative_passages.text: What balancing method can I apply to an imbalanced data set?
negative_passages.docid: 31680
negative_passages.text: How can I group numerical data into naturally forming "brackets"? (e.g. income)
negative_passages.docid: 77851
negative_passages.text: Should we apply normalization to test data as well?
negative_passages.docid: 52894
negative_passages.text: How to test if these two samples are from the same distribution?
negative_passages.docid: 117810
negative_passages.text: Transform Data to Desired Mean and Standard Deviation
negative_passages.docid: 84321
negative_passages.text: Pearson correlation of data sets with possibly zero standard deviation?
negative_passages.docid: 64536
negative_passages.text: How to correctly treat multiple data points per each subject
negative_passages.docid: 95555
negative_passages.text: Should I normalize word2vec's word vectors before using them?
negative_passages.docid: 135992
negative_passages.text: How can I adapt ANOVA for binary data?