MACHINE-LEARNING QUESTIONS

I hope this helps you . Both are correct. Method 1 uses standard deviation for spliiting the nodes and method 2 uses variance. Both s.d and variance are used since the target value is continuous.

TAG : machine-learning

Date : January 12 2021, 07:00 PM , By : ArmHead

What are the ways to calculate polarity of a sentence when using supervised learning algorithms?

wish helps you predict_proba() : gives you a probability score , if your case is a binary classification case , then you can set a threshold say

TAG : machine-learning

Date : January 09 2021, 05:38 AM , By : Bas

Changing the results of Kmeans algorithm

I wish this helpful for you The kmeans strategy tries to optimize the statistical quantity of the squared error. So what quantity would you want to optimize instead?On your data, you may then as well simple predefine the thresholds manually, rather t

TAG : machine-learning

Date : January 09 2021, 05:38 AM , By : 小和尚

SageMaker Estimator.fit() didn't pass the 'train' input to the Training instance

I think the issue was by ths following , When running training jobs in SageMaker the S3 URL containing your training data provided ends up being copied into the docker container (aka training job) from the specified url. Thus the environment variable

TAG : machine-learning

Date : January 08 2021, 10:52 AM , By : AJacques

Accuracy in logistic regression

With these it helps The notebook code is checking whether the actual category is in the top 3 returned from the model:

TAG : machine-learning

Date : January 07 2021, 07:50 AM , By : hammer_1968

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 : January 02 2021, 06:48 AM , By : smbrant

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 : January 02 2021, 06:48 AM , By : Govind Bhavan

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 : January 02 2021, 06:48 AM , By : SpittingCAML

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 : January 02 2021, 06:48 AM , By : chad

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 : January 02 2021, 06:48 AM , By : Nicholas Hunter

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 : January 02 2021, 06:48 AM , By : francisco santos

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 : January 02 2021, 06:48 AM , By : Mahyar Sepehr

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 : January 02 2021, 06:48 AM , By : MP.

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 : January 02 2021, 06:48 AM , By : bikefixxer

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 : January 02 2021, 06:48 AM , By : mgz

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 : January 02 2021, 06:48 AM , By : ezzze

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 : January 02 2021, 06:48 AM , By : ravibits

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 : January 02 2021, 06:48 AM , By : Vorinowsky

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 : January 02 2021, 06:48 AM , By : KingGuppy

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 : January 02 2021, 06:48 AM , By : pdkent

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 : January 02 2021, 06:48 AM , By : Richard

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 : January 02 2021, 06:48 AM , By : Hugo

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 : January 02 2021, 06:48 AM , By : LinnheCreative

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 : January 02 2021, 06:48 AM , By : user170635

Deep Learning + ML + CV > Requirements.txt file

I hope this helps you . Every time I create a virtual environment for machine learning project I just install this

TAG : machine-learning

Date : January 02 2021, 06:48 AM , By : ezzze

How to get the outline of the image detected (using cnn object detection) rather than rectangular box around it?

I hope this helps . I think you are looking for semantic segmentation. Object detection usually means finding a bounding box and a label for an object, while semantic segmentation is the problem of assigning a class label to each pixel in an image. O

TAG : machine-learning

Date : January 02 2021, 06:48 AM , By : yarry

I have done a classification problem where I am getting 99.9% accuracy but precision,recall,f1 is coming 0

Does that help This is happening because you have unbalanced dataset (99.9% 0's and only 0.1% 1's). In such scenario's using accuracy as metric can be misleading. You can read more about what metrics to use in such scenario's here

TAG : machine-learning

Date : January 02 2021, 06:31 AM , By : user187383

What is the best way to predict external test set?

will help you My Question is theoretical rather technical, hence I am not posting my code here because code is available at sklearn website itself. , The correct approach is

TAG : machine-learning

Date : January 01 2021, 05:04 PM , By : Francesco

How to get sentence embeddings from encoder in Fastai learner language model

This might help you This should give you the encoder(Which is an embedding layer) :learn.model[0].encoder

TAG : machine-learning

Date : January 01 2021, 05:01 PM , By : itsmegb

What are the steps should we take to analyze a dataset?

I hope this helps you . Your question is too general you need to specify more. What do you mean by the properties of the dataset? Nevertheless I'll try to answer what I understood from your question.After choosing what kind of problem you have (class

TAG : machine-learning

Date : January 01 2021, 06:46 AM , By : Kenny

MNIST model predicting test images incorrectly even though it had high training and testing accuracy

hope this fix your issue MNIST is not a dataset meant to learn a completely general digit recognition model, its just an academic benchmark, a very old one, so getting any kind of test accuracy close to 99% is very easy and it does not mean that the

TAG : machine-learning

Date : December 31 2020, 03:04 AM , By : Nigel

Is it possible to have low test error and high training error for a machine learning model?

fixed the issue. Will look into that further As learning models aim to reduce the training error (since the test set is not available while learning, hence the "test") this is very improbable, and i'd say unless you specifically create some example w

TAG : machine-learning

Date : December 31 2020, 03:04 AM , By : Ronnie Carlin

What would happen to training when validation_split is 0 while training a Keras model?

like below fixes the issue A validation set is used to detect overfitting, not having a validation set just means that you cannot detect overfitting. It does not mean that the model will automatically overfit. Remember that validation data is not use

TAG : machine-learning

Date : December 27 2020, 03:51 PM , By : sadboy

How to prepare images to train a ConvNet with Python/Keras?

may help you . My advice is that to start small and simple: start with employing common configs/parameters/methods and change them as needed based on the results of experiments you would perform. Should the images be cropped to exactly the object I w

TAG : machine-learning

Date : December 26 2020, 02:30 AM , By : Mihai Mocanu

What is RandomSearchCV and GridSearchCV?

around this issue I assume you mean the classes of cross validation (CV) strategies as used in sklearn. Cross validation is a method for evaluating models. One well known use case is to evaluate what set of hyper parameters to use in a model, such as

TAG : machine-learning

Date : December 25 2020, 01:01 PM , By : s8k

When training with Caffe should file lists be sorted?

This might help you Caffe supports line-by-line order or shuffle: https://github.com/BVLC/caffe/blob/2a1c552b66f026c7508d390b526f2495ed3be594/src/caffe/layers/image_data_layer.cppL51And to enable shuffling, you need to add a shuffle: true parameter i

TAG : machine-learning

Date : December 25 2020, 02:30 AM , By : NeedOptic

Why MAE is small but the plots doesnot shows clear relationship in regression analysis

hope this fix your issue The most common way to improve a model is to transform one or more variables, usually using a “log” transform.Transforming a variable changes the shape of its distribution. Typically the best place to start is a variable that

TAG : machine-learning

Date : December 24 2020, 10:01 PM , By : TRobison

What are GANs that take images as input instead of latent vectors?

this one helps. There is VAE-GAN, which likely can achieve what you want, you likely don't even need the "variational" part, You might also want to look into CycleGAN.

TAG : machine-learning

Date : December 23 2020, 07:08 AM , By : Frank

What is the difference between multi-task learning and MultiModel learning?

To fix this issue I think you mean Multimodal learning which deals with different kinds of data e.g. text, image, audio..etc and tries to learn a joint representation of the data.Multitask learning aims to learn multiple tasks at the same time. Those

TAG : machine-learning

Date : December 23 2020, 01:30 AM , By : Kocur

How does AI Platform (ML Engine) allocate resources to jobs?

this one helps. Alas, AI Platform Training can't automatically distribute your scikit-learn tasks. It basically just sets up the cluster, deploys your package to each node, and runs it.You might want to try a distributed backend such as Dask for scal

TAG : machine-learning

Date : December 22 2020, 08:01 PM , By : micate

Calculate SVM dual loss effeciently

To fix this issue I will give this question a shot, although I am not all that familiar with julia. The SVM is transforming the data you are giving it into a higher dimension so as to find a linear split between the classification of data. That bring

TAG : machine-learning

Date : December 22 2020, 04:30 PM , By : Raghu

How to save neural network model using joblib

Hope this helps It is not recommended to use pickle or cPickle to save a Keras model.You need just do: model.save(filepath)

TAG : machine-learning

Date : December 22 2020, 08:01 AM , By : Antony Briggs

What is the good RMSE (root-mean-square-error) value range to justify the efficiency of multivariate linear regression m

I wish this helpful for you Let me give you two examples having the same RMSE value: I'm trying to predict renting price for an apartment with renting price typically lying in range 500$-1000$. An RMSE value of 15$ could be argued to be a very low RM

TAG : machine-learning

Date : December 22 2020, 05:01 AM , By : Zelos

How to collect and filter images for image recognition?

should help you out You can search Kaggle for image recognition competitions such as cdiscount-image-classification-challenge. The data is usually available easily.

TAG : machine-learning

Date : December 21 2020, 11:30 PM , By : Matt Watson

How does input image size influence size and shape of fully connected layer?

this one helps. It seems like you are confusion spatial dimensions (height and width) of an image/feature map, and the "channel dimension" which is the dimension of the information stored per pixel.An input image can have arbitrary height and width,

TAG : machine-learning

Date : December 18 2020, 10:29 AM , By : noboruwatanabe

What do non-linear activation functions do at a fundamental level in neural networks?

it should still fix some issue First of all it's better to have a clear idea on why we use activation functions.We use activation functions to propagate the output of one layer’s nodes to the next layer. Activation functions are scalar-to-scalar func

TAG : machine-learning

Date : December 18 2020, 10:26 AM , By : Genipro

Convolutional Autoencoder in Pytorch for Dummies

it fixes the issue No, you don't need to care about input width and height with a fully convolutional model. But should probably ensure that each downsampling operation in the encoder is matched by a corresponding upsampling operation in the decoder.

TAG : machine-learning

Date : December 15 2020, 09:13 AM , By : sep

(cross) validation of CNN models - when to bring in test data?

it helps some times In your case I would remove 100 images for your test set. You should make sure that they resemble what you expect your final model to be able to handle. E.g. it should be objects which are not in the training or validation set, be

TAG : machine-learning

Date : December 10 2020, 07:09 AM , By : Monev

What does rank_test_score stand for from the model.cv_results_?

wish help you to fix your issue rank_test_score indicates the rank of a grid search parameter combination based on the mean_test_score.If you try N parameter combinations in your grid search, rank_test_score reaches from 1 to N.

TAG : machine-learning

Date : December 05 2020, 12:24 PM , By : Bado

How to see failed machine learning records

hope this fix your issue By using the GetColumn and CreateEnumerable methods, you can find the data that the model didn't predict correctly.After you the metrics, use the GetColumn method on the predictions that were from the test data set to get the

TAG : machine-learning

Date : December 01 2020, 04:52 PM , By : joshski

Ideal k value in kNN for classification

wish of those help In general notion, k is chosen to be sqrt(n),where n is the number of data-points,not the features. But the only way to validate your model is by the error on test data. What I generally do is, choose few random data-point from the

TAG : machine-learning

Date : November 28 2020, 09:01 AM , By : user142345

How to find if a data set can train a neural network?

Hope this helps There are only ad hoc ways to know if it is possible to learn a function with a differentiable network from a dataset. That said, these ad hoc ways do usually work. For example, the network should be able to overfit the training set w

TAG : machine-learning

Date : November 27 2020, 03:01 PM , By : JoeKaras

a summary of frequentist view in machine learning

will help you It is a bit hard, in my opinion, to make it brief. It's like banalizing two different visions of a world.Nevertheless, a very short reduction to a single argument can be this:

TAG : machine-learning

Date : November 24 2020, 03:41 PM , By : UnKnownUser

Use Merge layer (lambda/function) on Keras 2.0?

I hope this helps you . Kind of a weird way to implement a model.... (at least in keras 2...)It seems you should just use a lambda layer with a custom function.

TAG : machine-learning

Date : November 24 2020, 03:01 PM , By : Cube_Zombie

Multinomial naive bayes classification problem, normalization required?

wish helps you Your test set gives the same probability for both 10 and 20. Here's an example of how Naive Bayes calculates probability of each output category. https://medium.com/syncedreview/applying-multinomial-naive-bayes-to-nlp-problems-a-practi

TAG : machine-learning

Date : November 24 2020, 12:01 PM , By : Heals1ic

Could I turn a classification problem into regression problem by encoding the classes?

To fix this issue No, you can not. you can not define Cat < Dog or Dog < Cat. Regression works on that assumption. when you use regression for binary classification like logistic regression it is actually predicting the probability of a class which i

TAG : machine-learning

Date : November 24 2020, 05:49 AM , By : Mariocki

What does the embedding layer for a network looks like?

should help you out Embedding layer is just a trainable look-up table: it takes as input an integer index and returns as output the word embedding associated with that index:

TAG : machine-learning

Date : November 23 2020, 04:01 AM , By : Daljit Dhadwal

Use of perceptron for classification

This might help you The idea in multiclass variant of the Perceptron algorithm is pretty much the same as in the binary classification except for a few minor differences. In the multiclass classification with K classes, we will maintain a set of K we

TAG : machine-learning

Date : November 21 2020, 11:01 PM , By : Lucas Thompson

Weka IBk parameter details (distanceWeighting, meanSquared)

This might help you If one uses "no distance weighting", then the predicted value for your data points is the average of all k neighbors. For example

TAG : machine-learning

Date : November 21 2020, 09:01 AM , By : Shitic

Binary numbers instead of one hot vectors

wish help you to fix your issue It is fine if you encode with binary. But you probably need to add another layer (or a filter) depending on your task and model. Because your encoding now implicates invalid shared features due to the binary representa

TAG : machine-learning

Date : November 20 2020, 11:01 PM , By : esimran