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MACHINE-LEARNING QUESTIONS

Which machine learning classifier to choose, in general?
Which machine learning classifier to choose, in general?
will help you First of all, you need to identify your problem. It depends upon what kind of data you have and what your desired task is.
TAG : machine-learning
Date : November 24 2020, 07:00 PM , By : Akshat94
Issues in Convergence of Sequential minimal optimization for SVM
Issues in Convergence of Sequential minimal optimization for SVM
I wish this help you For most SVM implementations, training time can increase dramatically with larger values of C. To get a sense of how training time in a reasonably good implementation of SMO scales with C, take a look at the log-scale line for li
TAG : machine-learning
Date : November 19 2020, 07:01 PM , By : scooby
Hierarchy of meaning
Hierarchy of meaning
With these it helps It looks like you want to use something like the hypernym/hyponym relationships in WordNet, but without actually using WordNet due to language and domain specific coverage issues? That is, if you had the domain specific hypernym r
TAG : machine-learning
Date : November 10 2020, 07:00 PM , By : Abhinav Kumar
How can I use computer vision to find a shape in an image?
How can I use computer vision to find a shape in an image?
To fix this issue Practical issues Since you need a scale-invariant method (that's the proper jargon for "could be of various sizes") SIFT (as mentioned in Logo recognition in images, thanks overrider!) is a good first choice, it's very popular these
TAG : machine-learning
Date : October 28 2020, 08:00 PM , By : Kaléu Caminha
A good machine learning technique to weed out good URLs from bad
A good machine learning technique to weed out good URLs from bad
hop of those help? I think that steve and StompChicken both make excellent points: Picking the best algorithm is tricky, even for machine learning experts. Using a general-purpose package like Weka will let you easily compare a bunch of different app
TAG : machine-learning
Date : October 28 2020, 08:00 PM , By : user3854060
Is there a way to find the most representative set of samples of the entire dataset?
Is there a way to find the most representative set of samples of the entire dataset?
will be helpful for those in need This sounds like a stratification question - do you have pre-existing labels or do you plan to design the labels based on the sample you're constructing?If it's the first scenario, I think the steps in order of impor
TAG : machine-learning
Date : October 19 2020, 06:10 PM , By : Yonggang LIU
Interactive learning
Interactive learning
I think the issue was by ths following , You can do this but it will be a very intensive task if you plan on retraining the model on the whole data again and again if it is on a daily basis. Instead of retraining the model completely, you should try
TAG : machine-learning
Date : October 18 2020, 06:10 AM , By : LunaGao
Wor2vec fine tuning
Wor2vec fine tuning
may help you . I am new at working with word2vec. I need to fine tune my word2vec model. , Is this correct?
TAG : machine-learning
Date : October 14 2020, 01:00 PM , By : Zaher
Optimize deep Q network with long episode
Optimize deep Q network with long episode
hope this fix your issue Honestly, there is no effective way to know how to optimize this system without knowing specifics such as which computations are in the reward function or which programming design decisions you have made that we can help with
TAG : machine-learning
Date : October 14 2020, 01:00 AM , By : Lennix
What is K Max Pooling? How to implement it in Keras?
What is K Max Pooling? How to implement it in Keras?
wish of those help As per this paper, k-Max Pooling is a pooling operation that is a generalisation of the max pooling over the time dimension used in the Max-TDNN sentence model and different from the local max pooling operations applied in a convol
TAG : machine-learning
Date : October 13 2020, 07:00 AM , By : bNew3800
Should Feature Selection be done before Train-Test Split or after?
Should Feature Selection be done before Train-Test Split or after?
it helps some times The conventional answer 1 is correct here; the arguments in the contradicting answer 2 do not actually hold.When having such doubts, it is useful to imagine that you simply do not have any access in any test set during the model f
TAG : machine-learning
Date : October 13 2020, 06:00 AM , By : Paris
How to squish a continuous cosine-theta score to a discrete (0/1) output?
How to squish a continuous cosine-theta score to a discrete (0/1) output?
should help you out As said, I would like to use variables such as p, and the cosine theta score in order to produce an accurate discrete binary label, either 0 or 1.
TAG : machine-learning
Date : October 12 2020, 05:00 AM , By : Mohamed Hamed
How can less amount of data lead to overfitting?
How can less amount of data lead to overfitting?
hope this fix your issue In general, the less data you have the better your model can memorize the exceptions in your training set which leads to high accuracy on training but low accuracy on test set since your model generalizes what it has learned
TAG : machine-learning
Date : October 11 2020, 08:00 PM , By : Vivek
Does BERT implicitly model for word count?
Does BERT implicitly model for word count?
wish help you to fix your issue BERT by default considers "word-piece" tokenization and not "word" tokenization. BERT makes available the max-sequence length attribute, which is responsible to limit the number of word-piece tokens in a given sentence
TAG : machine-learning
Date : October 10 2020, 10:00 PM , By : Ace-Tang
Correlation between time series
Correlation between time series
help you fix your problem A general good rule in data science is to first try the easy thing. Only when the easy thing fails should you move to something more complicated. With that in mind, here is how you would compute the Pearson correlation betwe
TAG : machine-learning
Date : October 10 2020, 06:00 PM , By : Patrick S.
Train spaCy's existing POS tagger with my own training examples
Train spaCy's existing POS tagger with my own training examples
I wish did fix the issue. The English model is trained on PTB tags, not UD tags. spacy's tag map gives you a pretty good idea about the correspondences, but the PTB tagset is more fine-grained that the UD tagset:https://github.com/explosion/spaCy/blo
TAG : machine-learning
Date : October 10 2020, 03:00 AM , By : Sara
what does lightgbm python Dataset reference parameter mean?
what does lightgbm python Dataset reference parameter mean?
Does that help The idea of "validation data should be aligned with training data" is simple : every preprocessing you do to the training data, you should do it the same way for validation data and in production of course. This apply to every ML algor
TAG : machine-learning
Date : October 09 2020, 11:00 PM , By : Juanjo Gonzalez
Keras Embedding Layer: keep zero-padded values as zeros
Keras Embedding Layer: keep zero-padded values as zeros
this will help Well, you're eliminating the computation of the gradients of the weights related to the padded steps. If you have too many padded steps, then the embedding weights regarding the padding value will participate in a lot of calculations a
TAG : machine-learning
Date : October 09 2020, 11:00 PM , By : Amogh Kanade
What are the pros and cons of using DVC and Pachyderm?
What are the pros and cons of using DVC and Pachyderm?
this one helps. It depends on what are you trying to accomplish.DVC will help you with organizing the ML experimentation process.
TAG : machine-learning
Date : October 09 2020, 10:00 AM , By : atekiryu
How to convert Pytorch model parameters to long datatype?
How to convert Pytorch model parameters to long datatype?
fixed the issue. Will look into that further Most nn modules do not support long (integer) operations, e.g., convolutions, linear layer etc. Therefore, you cannot "cast" a model to torch.long.
TAG : machine-learning
Date : October 09 2020, 04:00 AM , By : MelissaJames
How do I create a feature vector if I don’t have all the data?
How do I create a feature vector if I don’t have all the data?
like below fixes the issue When I read this question, it seems that you may have confused with feature and label. You said that you want to predict whether a new item is "gasHeated", then "gasHeated" should be a label rather than a feature.
TAG : machine-learning
Date : October 08 2020, 04:00 PM , By : w3bster95
What is the best way to use golden feature in machine learning model?
What is the best way to use golden feature in machine learning model?
it fixes the issue You can have an ensemble modelling approach.Here is what it would look like:
TAG : machine-learning
Date : October 07 2020, 03:00 PM , By : 余程洋
Very low performance even after oversampling dataset
Very low performance even after oversampling dataset
help you fix your problem The first mistake in your code is when you are transforming data into standard format. You only need to fit StandardScaler once and that is on X_train. You shouldn't refit it on X_test. So the correct code will be:
TAG : machine-learning
Date : October 07 2020, 05:00 AM , By : ktomlinson
The Difference between One Hot Encoding and LabelEncoder?
The Difference between One Hot Encoding and LabelEncoder?
around this issue I am working on a ML problem to predict house prices and Zip Code is one feature which will be useful. I am also trying to use Random Forest Regressor to predict the log of the price. , Like the link says:
TAG : machine-learning
Date : October 07 2020, 01:00 AM , By : Javier López
What is the difference between probabilistic programming vs. probabilistic machine learning?
What is the difference between probabilistic programming vs. probabilistic machine learning?
will help you I guess there is some vagueness between the two terms but my take on them is the following:Probabilistic Programming it is expressing probabilistic models as computer programs that generate data (i.e. simulators).
TAG : machine-learning
Date : October 06 2020, 05:00 PM , By : S Yoon
What value do I set for the decay parameter of any optimizer in Keras
What value do I set for the decay parameter of any optimizer in Keras
I wish did fix the issue. You just need to instantiate Adam and set the parameters in the constructor (__init__):
TAG : machine-learning
Date : October 06 2020, 01:00 AM , By : Alren Tristan Sese V
Connecting Keras model with no output
Connecting Keras model with no output
it helps some times Yes , Using the Keras functional API brings you all possibilities. check it out herehttps://keras.io/getting-started/functional-api-guide/multi-input-and-multi-output-models
TAG : machine-learning
Date : October 05 2020, 04:00 AM , By : tech_geezy
Why should I reduce the skewness of my data before applying a Machine Learning algorithm?
Why should I reduce the skewness of my data before applying a Machine Learning algorithm?
hop of those help? "What is the problem with skewed data?". There is not a problem at all. The question may rather be why skewed data may cause problems in some machine learning models. It comes solely down to how the model utilizes the data for appr
TAG : machine-learning
Date : October 04 2020, 02:00 AM , By : Abdullah Ansari
Do features in Sci-kit learn have to be the same length
Do features in Sci-kit learn have to be the same length
Hope that helps The features need to be of the same length i.e. You should have no missing values in the dataset. Some models handle missing values internally but it's better to handle those. There are a number of options that you have. Let's list ea
TAG : machine-learning
Date : October 03 2020, 11:00 PM , By : godwind
How to conveniently control features in Nvidia StyleGAN?
How to conveniently control features in Nvidia StyleGAN?
should help you out In case someone else looks for the same thing.Finally I managed to find something very close to what I was looking for - a project that allows to control StyleGAN facial features through UI:
TAG : machine-learning
Date : October 03 2020, 01:00 AM , By : Fehmi Cesur
Is a Conditional Random Field, on a Named Entity Recognition task, bi-directional?
Is a Conditional Random Field, on a Named Entity Recognition task, bi-directional?
I hope this helps . No.For example, a linear-chain conditional random field looks like this:
TAG : machine-learning
Date : October 02 2020, 07:00 AM , By : B. Fekete
Text classification based on optical character recognition
Text classification based on optical character recognition
Hope this helps This problem falls within the realms of natural language processing / text classification
TAG : machine-learning
Date : October 01 2020, 11:00 AM , By : user6065115
How to use K.get_session in Tensorflow 2.0 or how to migrate it?
How to use K.get_session in Tensorflow 2.0 or how to migrate it?
like below fixes the issue Tensorflow 2.0 does not expose the backend.get_session directly any more but the code still there and expose for tf1.https://github.com/tensorflow/tensorflow/blob/r2.0/tensorflow/python/keras/backend.pyL465
TAG : machine-learning
Date : September 30 2020, 03:00 PM , By : Jannat
How to use cross-validation and early stopping together?
How to use cross-validation and early stopping together?
will help you Even when you do not use Early Stopping, every time you use Cross-Validation you have a different model in each fold: the model has different parameters and different results, but that's the point of CV. You can use ES without any parti
TAG : machine-learning
Date : September 30 2020, 08:00 AM , By : Caio Costa
Time Series Forecasting: weekly vs daily predictions
Time Series Forecasting: weekly vs daily predictions
Hope this helps This is a standard daily time series problem where there is a day-of-week seasonality. If you are using R, you could make the time series a ts object with frequency = 7 and then use auto.arima() from the forecast package to forecast i
TAG : machine-learning
Date : September 28 2020, 10:00 PM , By : Vegeta
How to extract coefficients from fitted pipeline for penalized logistic regression?
How to extract coefficients from fitted pipeline for penalized logistic regression?
it helps some times Have a look at the scikit-learn documentation for Pipeline, this example is inspired by it:
TAG : machine-learning
Date : September 28 2020, 10:00 AM , By : Musila
Is Machine Learning+Neural Layers=Deep Learning?
Is Machine Learning+Neural Layers=Deep Learning?
To fix this issue Machine learning: Machine learning is the science of making computers learn and act like humans by feeding data and information without being explicitly programmed.
TAG : machine-learning
Date : September 27 2020, 11:00 AM , By : krishna
Geometric Mean instead of Simple Mean
Geometric Mean instead of Simple Mean
With these it helps Use of geometric mean: A geometric mean is useful in machine learning when comparing items with a different number of properties and numerical ranges. The geometric mean normalizes the number ranges giving each property equal weig
TAG : machine-learning
Date : September 27 2020, 07:00 AM , By : Rajath Tellapuram
In Keras, what is a "dense" and a "dropout" layer?
In Keras, what is a "dense" and a "dropout" layer?
I wish this helpful for you In short, a dropout layer ignores a set of neurons (randomly) as one can see in the picture below. This normally is used to prevent the net from overfitting. The Dense layer is a normal fully connected layer in a neuronal
TAG : machine-learning
Date : September 27 2020, 05:00 AM , By : Paul Hotchin
Getting a specific random forest variable importance measure from mlr package's resample function
Getting a specific random forest variable importance measure from mlr package's resample function
Any of those help You provide a lot of specifics that do not actually relate to your question, at least how I understood it. So I wrote a simple MWE that includes the answer. The idea is that you have to write a short wrapper for getFeatureImportance
TAG : machine-learning
Date : September 26 2020, 03:00 PM , By : Ian Bensley
How to Multi-Head learning
How to Multi-Head learning
wish of those help I have about 5 models that work pretty well trained individually but I want to fuse them together in order to have one big model. I'm looking into it because one big model is more easy to update (in production) than many small mode
TAG : machine-learning
Date : September 26 2020, 11:00 AM , By : Oleksii Koniev
Simple policy gradients (REINFORCE) overfits one action when playing Atari Breakout
Simple policy gradients (REINFORCE) overfits one action when playing Atari Breakout
fixed the issue. Will look into that further We ran into a similar problem while training Breakout with VPG (Vanilla Policy Gradient). The solution was to enforce entropy loss over the following Entropy loss over the policy model output (Penalise sel
TAG : machine-learning
Date : September 26 2020, 10:00 AM , By : sakura
2.3 ratio between Pytorch BCEloss and my own "log" calculations
2.3 ratio between Pytorch BCEloss and my own "log" calculations
I wish this help you This is because in Excel the Log function calculates the logarithm to the base 10. The standard definition of binary cross entropy uses a log function to the base e. The ratio you're seeing is just log(10)=2.302585
TAG : machine-learning
Date : September 26 2020, 09:00 AM , By : Mahavir Amiyaranjan
GCP - Creating a Dataflow (Pub/Sub -> prediction(ML model) -> BigQuery/Firebase)
GCP - Creating a Dataflow (Pub/Sub -> prediction(ML model) -> BigQuery/Firebase)
may help you . There is several ways to address your use case. First of all, I'm not sure that Dataflow is required. Dataflow is perfect for data transformation, or data comparison as described in the article, but I'm not sure that is your use case.
TAG : machine-learning
Date : September 25 2020, 10:00 PM , By : apostol
Why is make_friedman1 used?
Why is make_friedman1 used?
Any of those help If make_friedman1 asked here is the one in sklearn.datasets then it is the function which generates the “Friedman 1” regression problem. Here inputs are 10 independent variables uniformly distributed on the interval [0,1], only 5 ou
TAG : machine-learning
Date : September 25 2020, 10:00 AM , By : MickR
How I make pytorch read the numpy format?
How I make pytorch read the numpy format?
wish of those help I can't confirm but I believe your problem will be solved by changing:
TAG : machine-learning
Date : September 24 2020, 08:00 PM , By : Just A Person
Compare results from Julia MLJ models
Compare results from Julia MLJ models
around this issue I'd like to train 3 models in MLJ.jl: ARDRegressor, AdaBoostRegressor, BaggingRegressor , There are a few issues in running your last code block.
TAG : machine-learning
Date : September 22 2020, 05:00 PM , By : alimoew2w
how to draw a correct hyper plane in python
how to draw a correct hyper plane in python
Hope this helps One way is to use the decision_function from the classifier and plot some level line (level=0 correspond to your hyperplane). Here is some code.
TAG : machine-learning
Date : September 22 2020, 02:00 AM , By : badghost
Is this possible to predict the lottery numbers (not the most accurate)?
Is this possible to predict the lottery numbers (not the most accurate)?
wish of those help It is impossible. The lottery numbers are random - actually to be more specific, the system is chaotic. You would require the initial configuration (positions etc) to insane (possibly infinite) precision to be able to make any pred
TAG : machine-learning
Date : September 21 2020, 10:00 PM , By : Mi Reader
Encoding numeric nominal values in machine learning
Encoding numeric nominal values in machine learning
This might help you it's called normalization and the goal of normalization is to change the values of numeric columns in the dataset to use a common scale, without distorting differences in the ranges of values or losing information.
TAG : machine-learning
Date : September 21 2020, 12:00 AM , By : yaox12
TESPAR Coding Method - how to generate the alphabet?
TESPAR Coding Method - how to generate the alphabet?
I hope this helps you . considering your problem, maybe you should try a density-based clustering approach
TAG : machine-learning
Date : September 20 2020, 07:00 PM , By : Havez Vazirani Al Ka
What is the purpose of cross-validation if the model is thrown away each iteration
What is the purpose of cross-validation if the model is thrown away each iteration
I think the issue was by ths following , You do cross-validation to get an estimate of how well your model will perform on unseen data. The point is to see how well it generalises.Once you've done cross-validation and are happy with your score, you c
TAG : machine-learning
Date : September 20 2020, 05:00 PM , By : Luke Brown
PyTorch Model can only recognize birds when birds are close to camera
PyTorch Model can only recognize birds when birds are close to camera
hope this fix your issue Your dataset is biased toward birds at a certain scale, i.e., their size, in pixels, span a very small range (you can verify this).Center-cropping the images will not change that - the size of the birds (in pixels) will not c
TAG : machine-learning
Date : September 20 2020, 05:00 PM , By : Samuel Dubrez
How does adding noise to output avoid overfitting on training points?
How does adding noise to output avoid overfitting on training points?
it helps some times Why does it prevent overfitting?Noise destroys information. Your data becomes harder to fit, thus harder to over-fit. The extreme case is pure noise and your classifier will learn to ignore the input and predict a fixed probabilit
TAG : machine-learning
Date : September 20 2020, 03:00 PM , By : John
Fast.Ai EarlyStoppingCallback does not work
Fast.Ai EarlyStoppingCallback does not work
fixed the issue. Will look into that further It keeps track of the best error rate and compares the min_delta to the difference between this epoch and that value:
TAG : machine-learning
Date : September 20 2020, 03:00 PM , By : gstein
What is the difference between Logistic Regression and Single Neuron Perceptron?
What is the difference between Logistic Regression and Single Neuron Perceptron?
wish help you to fix your issue If the single neuron perceptron has a sigmoid activation function, then there is no difference.In fact, I think Andrew Ng gives logistic regression as his first example of a neural network in his coursera course.
TAG : machine-learning
Date : September 19 2020, 07:00 PM , By : Holo
Naive Bayes classifier for movie reviews has very low accuracy, despite several attempts of feature selection
Naive Bayes classifier for movie reviews has very low accuracy, despite several attempts of feature selection
this one helps. Text preprocessing is very important here. Removal of stop words only is not enough, I think you should consider the following: convert the text to lowercase removal of punctuation Apostrophe lookup ("'ll" -> " will"', "'ve" -> " have
TAG : machine-learning
Date : September 14 2020, 02:00 PM , By : xxm
Explanation of feature descriptors in computer vision and machine learning
Explanation of feature descriptors in computer vision and machine learning
it fixes the issue Features are the information extracted from images in terms of numerical values that are difficult to understand and correlate by human. Suppose we consider the image as data the information extracted from the data is known as feat
TAG : machine-learning
Date : September 13 2020, 10:00 PM , By : 髙橋翔
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