Questions tagged [fuzzy-logic]
Fuzzy logic is logic handling uncertainty by using as truth values a real number between 0 and 1 to represent less or more certainty about a variable. Fuzzy operators similarly work with degrees of truth.
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Implementing Fuzzy Matching and NLP for Transaction Classification
I’m a trainee at a fintech startup, and I’m working on a project that involves classifying transactions using Natural Language Processing (NLP) and fuzzy matching techniques. The main goal is to ...
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ANFIS Model, tips about improving performance
I have a question regarding about improving the performance of an ANFIS (adaptive neuro Fuzzy inference system) model.
In MATLAB, I have been training a model with 5 inputs, with 816 data point for ...
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Academic name of dataset preparation method with hierarchical-learned labels? - E.g., cold→half-cooked→cooked
What's the name of the dataset preparation method indicating hierarchical ontologies?
Assume photos of cold, half-cooked, and fully-cooked chickens. Annotate with temperature data. E.g., at current ...
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Fuzzy Inference System IF-THEN Rules
I am currently doing a fuzzy inference system project in Python, however, a question came up.
I have to do it the hard way, that is, do it step by step, as done here: https://pythonhosted.org/scikit-...
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Levenshtein distance vs simple for loop
I have recently begun studying different data science principles, and have had a particular interest as of late in fuzzy matching. For preface, I'd like to include smarter fuzzy searching in a ...
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Fuzzy Address Matching using Rapid Fuzz
I am using RapidFuzz for matching US Addresses from two separate datasets.
I was able to get the results that I was hoping for using the below code:
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Problem in convergence of hebbian learning approach for Fuzzy Cognitive Map
I was trying to learn Fuzzy Cognitive Map by Active Hebbian Learning approach from here. What I have understand is that the model learns iteratively, at each step a new concept values enters and tune ...
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Algorithm to determine a single output value based on multiple input values [closed]
The main challenge is the lack of data.
Input values come from tests results of patients. A patient takes a breath test at an interval during a timespan. The result values can range from 0 to ~200, ...
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Fuzzy and FuzzyWuzzy: what are the differences in text comparison?
I have found a lot of information about fuzzy logic, but less information about fuzzywuzzy. I would like to know more about this, the function which determines the logic, if possible, and understand ...
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Are there any tools/ python packages for Fuzzy Grouping?
I'm trying to get to a tool for Fuzzy Grouping as I do not have a reference column for matching the string. Is there any package on Python or R?
I looked at a package called textpack but the results ...
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What is the generalization of binary/boolean matrix factorization to fuzzy logics called?
Given a matrix of boolean values $\mathbf{X} \in \mathbb{B}^{M \times N} = \{\top, \bot\}^{M \times N}$, the binary/boolean matrix factorization (BMF) problem is to find $\mathbf{U} \in \mathbb{B}^{M \...
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How fit_transform, transform and TfidfVectorizer works
I'm a machine learning beginner and I tried to use the cosine similarity on fuzzy matching purpose. In the following example I want to compare 'data_dirty' with 'data_clean' :
When I have to ...
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Fuzzily join two large sets of postal addresses
I have two tables of postal address information - the one is about 2 million records, the other roughly 40 million. They have quite bad quality, and also are not quite compatible with each other (...
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What's the difference between multi label classification and fuzzy classification?
Is it just the between academics and practitioners in term usage?
Or is theoretical difference of how we consider each sample: as belonging to multiple classes at once or to one fuzzy class?
Or ...
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what is fuzzy svm?
I have to solve this question for my homework but I don't get how to formulate svm to FSVM. can someone please guide me?
What is your idea to have a model of SVM classifier in which instances can ...
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Fuzzy Clustering for Categorical Data
I have a dataset in which each feature is either 0 or 1 (like BBOW). I want to cluster the data such that one point can belong to more than one cluster(soft assignment).
I searched about this and I ...
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Fuzzy logic for classification
I am trying to implement fuzzy logic system to classifiy a dataset with 12 inputs and 1 ouput.
I wanna understand as how to fuzzify inputs, in particular how we set intervals or segments in order to ...
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What algorithm could be used to fuzzy merge multiple datasets?
Problem Description
I have several tables that are related but do not share any unique key. I've come across this problem several times with customer data in separate source systems that needs to be ...
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Fuzzy rule based system: Should rules contain all inputs and outputs?
I am trying to design an FRBS using Matlab fuzzy tool box. The fuzzy system will be used to predict player's type based on the inputs and a set of rules defined by experts.
I have 6 inputs and 4 ...
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[R]Fuzzy C-Means, different between ppclust vs e1071?
no. of cluster = 10, data points = 6000
library(ppclust)
cm <- fcm(x,centers = cen)
takes ~ 10 minutes
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Plagiarism detection with Python
Background
Using Python, I need to score the existence of a quote, containing around 2-7 words, a longer text. The quote doesn't have to match the text precisely, but similar words should have the ...
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Data Matching Using Machine Learning
I have around 4000 customer records and 6000 user records and about 3000 customer records match leaving 1000 unmatched customers. I have created a fuzzy matching algorithm using Levenshtein and ...
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What is the rationale to use weights and biases in a neural network?
Searched a lot of research papers, blogs and videos but couldnt find an acceptable answer for choosing the weights and biases in neural network. Few people have mentioned to use weights randomly but ...
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datasets for fuzzy clustering
By now i thought that fuzzy clustering can be applied to any kind of data-sets but now i have heard that it can be applied only to specific data-sets that involve the concept of probability, is that ...
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Can inferencing come from incomplete rule sets?
I have some data for medical diagnosis, consisting of some rules about relationship of diseases and their symptoms, for example disease D1 frequently has symptom S1 or disease D2 rarely has symptom S1....
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Check similarity of table/csv of Product Names
We've got a list of approximately 18,000 product names (they're from 80-90 sources, so quite a few that are similar but not duplicates - these were picked as DISTINCT from a table) unfortunately there ...
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Is there a parallel to record linkage/entity resolution where ML can be applied to the data for schema matching?
In the context of collecting disparate data sets holding similar information, are their examples of algorithms being able to resolve attributes of records being similar (while their values are ...
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Fuzzy Inference system in R
I want to use R for implementing a fuzzy inference system. There are 4 input variables and one output. Each rule is dependent on all input variables and based on there membership the output class is ...
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Fuzzy Rules with more than two variable in python
I am trying to build a fuzzy inference system in Python using skfuzzy library. I have 4 variables depending on which output class is decided.
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Why does image segmentation benefit from fuzzy clustering?
In many image processing papers, I've seen that they used fuzzy logic for segmentation
I wonder how fuzzification impact the result that made Fuzzy-C-Means better than ordinary K-Means.
PS. If ...
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Does anyone have any thought how come the fuzzy rules can be verified and validated?
Fuzzy logic was utilized to derive a performance indicator of some manufacturing facilities in an uncertain environment. There are some historical data obtained from some manufacturing facilities’ ...
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