Questions tagged [data]
Questions mostly concerned with managing data, without focus on pre-processing or modelling.
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How is a splitting point chosen for continuous variables in decision trees?
I have two questions related to decision trees:
If we have a continuous attribute, how do we choose the splitting value?
Example: Age=(20,29,50,40....)
Imagine that we have a continuous attribute $f$...
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17
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5
answers
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Do modern R and/or Python libraries make SQL obsolete?
I work in an office where SQL Server is the backbone of everything we do, from data processing to cleaning to munging. My colleague specializes in writing complex functions and stored procedures to ...
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3
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439
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Train classifier on balanced dataset and apply on imbalanced dataset?
I have a labelled training dataset DS1 with 1000 entries. The targets (True/False) are nearly balanced. With sklearn, I have tried several algorithms, of which the GradientBoostingClassifier works ...
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1
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2
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Date transformation for KNN
I have data set with date features like 01/01/2019 and I would like to use KNN. However, I cannot find a good transformation for dates that has a meaningful ...
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2
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How much data are sufficient to train my machine learning model?
I've been working on machine learning and bioinformatics for a while, and today I had a conversation with a colleague about the main general issues of data mining.
My colleague (who is a machine ...
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2
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How does the validation_split parameter of Keras' fit function work?
Validation-split in Keras Sequential model fit function is documented as following on https://keras.io/models/sequential/ :
validation_split: Float between 0 and 1. Fraction of the training data
...
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12
votes
4
answers
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Interpreting Decision Tree in context of feature importances
I'm trying to understand how to fully understand the decision process of a decision tree classification model built with sklearn. The 2 main aspect I'm looking at are a graphviz representation of the ...
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12
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1
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Do I have to standardize my new polynomial features?
I have a vector X with n features previously standardized.
If I want to generate new polynomial features (let say adding square features), do I need to do another standardization on these new ...
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6
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Generate timeseries data
Training would be bad if training data is not sufficient. Techniques like SMOTE or ADASYN can be used for oversampling. For image data, we can blur or change the angle to generate more samples from ...
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5
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4
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Missing Values in Data [duplicate]
I have experienced that most of the datasets contain missing values, which make our task bit challenging.
Please let me know how to fill up those missing values in an efficient way? and is there any ...
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6
votes
2
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Merging large CSV files in pandas
I have two CSV files (each of the file size is in GBs) which I am trying to merge, but every time I do that, my computer hangs. Is there no way to merge them in chunks in pandas itself?
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1
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Purpose of weights in neural networks
I'm beginner at Neural Networks. After reading multiple articles on wikipedia, i've seen the term "weight" being used a lot, although it is a little confusing.
I know, that before the inputs are ...
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1
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Decision Tree used for Calculating Precision, Accuracy, and Recall, class breakdown question
I am creating decision trees modeling data that looks like this.
...
- 153
2
votes
2
answers
657
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Best Programming Language for Data Science [closed]
I'm learning JS, HTML and CSS, but I doubt JS is very good at Data Analysis. So, what would you guys recommend me learning to start my "career" in Data Science? What's the best programming language ...
- 123
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2
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What is valued more in the data science job market, statistical analysis or data processing?
Not sure if this question is OT here. If it is, perhaps move it to meta? If not:
I'm trained in classical statistics, work in research, and have learned much (and taught) machine learning. I've ...
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3
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3k
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Why is a correlation matrix symmetric?
I'm sorry for being so weak in math. (I'm a student) For eg. this is a correlation matrix.
...
3
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2
answers
198
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Domain-specific data science programs
I am looking for domain-specific data science programs (as a major, not a minor or specialization). I found programs in bio-statistics (and other disciplines in public health), MS in marketing ...
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3
votes
2
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802
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Do i need to handle missing values before EDA?
I am working on a data set and there is an interesting column with missing values, but I don't want to discard the rows (so as not to lose data from other columns) or do imputation (so as not to ...
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2
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2
answers
220
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How to handle non ordinal Features like Gender,Language,Region etc? Ordinal Encoding or one-hot encoding?
I see that usually, while preparing the dataset. Usually, data scientists convert non-ordinal features like Gender or Language in a dataset using LabelEncoder/ordinalEncoder. Ideally, they should have ...
2
votes
1
answer
383
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SMOTE oversampling for class imbalanced dataset introduces bias in final distribution
I have a problem statement where percentage of goods (denoted by 0) is 95%, and for bads (denoted by 1) it is 5% only. One way is to do under sampling of goods so that model understands the patterns ...
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2
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2
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115
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in which case can I say that the data are bad and I ll achieve nothing using machine learning on it
general Infos about my dataset: I have 40k data points and 5 features.
I'm doing regression and trying to build a model that can predict the error of a GPS. for example imagine that your vehicle GPS ...
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1
vote
1
answer
99
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Best practice - memory management when data wrangling
I was wondering what are the best resources to learn the best practice when it comes to memory management. For example, lets say I have the following code below:
...
1
vote
1
answer
2k
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Data augmentation for multiple output heads in Keras
I have a transfer learning based two output classification problem. So, accordingly, I have formatted my data to have X_train as a ...
1
vote
1
answer
136
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Computing Jaccard Similarity between two documents
Data Mining:
Compute the Jaccard similarity of D1 and D2 on 2-shingles is. Sim(D1,D2) =
D1 = the quick brown fox jumps over the lazy dog
D2 = jeff typed the quick brown dog jumps over the lazy fox ...
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1
vote
2
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Problem with converting string to dummy variables
I'm new in data science, I have data which want to work on it, I omitted extra columns and convert it to 4 columns ( Product, Date, Market, Demand ) . in this data Product and Market are string, I ...
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0
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1
answer
144
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How to distort data in a clever way? [closed]
For example, I have some time series. How can I change my data, so it will not be obvious to understand what was original values?
Ideally transformation would allow to revert and reconstruct ...
0
votes
1
answer
170
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Can we have a dataset with slight difference in target values for same value of feature variable?
I am trying to generate a dataset which involves 1 feature variable(X) and 1 target variable(y).
The feature variable ...
0
votes
1
answer
102
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Image data augmentation with this function
Following function is from http://scikit-learn.org/stable/auto_examples/neural_networks/plot_rbm_logistic_classification.html#sphx-glr-auto-examples-neural-networks-plot-rbm-logistic-classification-py ...
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