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H: How to deal with Nominal categorical with label encoding?
So if my dataset looks like this:
names life_style instrument times
0 sid creative piano 1.5
1 aadi artistic guitar 1.4
2 aman traveller drum 1.1
3 sid artistic guitar 1.5
4 aadi creative drum 1.4
N... |
H: LSTM Model for predicting the minutely seasonal data of the day
I am making a model for predicting the network traffic volume for our data center.
Let me describe my dataset first. At this time, we have the model of 90 days, on each day, we record the network traffic volume every minute. And this data also has the... |
H: How to read html tables under multiple headers and combine them in a single pandas dataframe?
I have an html file like this:
<h1>Group 1</h1>
<table>
<tr>
<td>Col1</td>
<td>Col2</td>
<td>Col3</td>
</tr>
<tr>
<td>ValA</td>
<td>ValB</td>
<td>ValC</td>
</tr>
</table>
<h1>Group 2</h1>
<t... |
H: the error occurred while selecting feature using recursive feature elimination in sklearn
I tried to rank the feature using recursive feature elimination in sklearn. However, I got this error when using RFE. here are the error and code information.
from sklearn import svm
x_vals = data['all_data'][:,0:320]
y... |
H: What is the best performance metric used in balancing dataset using SMOTE technique
I used smote technique to oversample my dataset and now I have a balanced dataset. The problem I faced is that the performance metrics; precision, recall, f1 measure, accuracy in the imbalanced dataset are better performed than with... |
H: What is the differences between normal equation and gradient descent for polynomial regression
I'm new to machine learning and willing to study and work with machine learning. It just that I still don't get to understand the benefits of using the normal equation in some occasion in comparison with gradient descent.... |
H: Where can we find the application of bayes's theorem in Bayesian optimiation with gaussian processing
I am trying to learn bayesian optimisation by following this tutorial.
However, until now I don't get the relation between bayes's theorem to the gaussian process formalism.
Any ideas?
AI: It is a 49 page long pape... |
H: How to interpret Hashingvectorizer representation?
I cannot really understand the logic behind Hashingvectorizer for text feature extraction. I can follow the logic of Bag of Word or TFiDF where the features are values for all/certain words/N-grams per document and as such one can compute (dis)similarity between th... |
H: Understanding the filter function in Convolution Neural Networks
I am trying to follow the following tutorial accessible with this link.
Under the 3rd Heading, "3. Visualize the Activation Maps for Each Filter", we can see the following function:
def apply_filter(img, index, filter_list, ax):
# set the weights ... |
H: difference in between CNN and Inception v3
What is the difference in between the inception v3 and Convolutional neural network?
AI: The Inception models are types on Convolutional Neural Networks designed by google mainly for image classification. Each new version (v1, v2, v3, etc.) marks improvements they make upo... |
H: Isn't the depth of a convolutional layer, the number of colors (or colorspace size)?
I have been going through a CNN tutorial and noticed that depth of a convolutional layer is equal to the number of filters. But, shouldn't the depth be the number of colors in the image? I mean, if it's RGB then, depth is 3 right? ... |
H: When to remove correlated variables
Can somebody please suggest what is the correct stage to remove correlated variables before feature engineering or after feature engineering ?
AI: You do not want to remove all correlated variables. It is only when the correlation is so strong that they do not convey extra inform... |
H: why this naming convention for padding as "Same" and "Valid" in keras
I was going through CNN's and found that padding argument should be set to "Valid" if i need no padding and "Same" if i need padding. But, it doesn't make any sense to me. Why can't keras development team just put "Padding = True", is there a spe... |
H: How to deal with Optional Input
I'm from the vision world and only worked with pixels from 0-255, ignoring any side effects. My current problem is different, in the way that I cannot rely on the input data.
What my problem is:
I have a number of inputs. Each input is categorical (for now) and optional. For example... |
H: 4 Class Classification - Machine Learning Model
I have a data set which contains nearly 150 features and 60k data. And my target feature is continuous variable represents hours. I divided this period into 4 categories of user engagement (4 ranges of hours). Implement GA with SVM, GA with logistic regression, Random... |
H: Aggregating small values in a frequency bar plot
I have a pandas Series of sorted percentage values like this :
A -> 0.001
B -> 0.0012
C -> 0.0015
...
H -> 0.02
I -> 0.03
J -> 0.041
...
X -> 0.12
Y -> 0.31
Z -> 0.4
(I typed those by hand, I am not familiar with how to type those python outputs in DSSE, sorry! If a... |
H: What's the difference of stateless LSTM and a normal feed-forward NN?
From what I understand, the whole point of LSTM is for the network to establish long-term dependencies in the data, i.e. an event happening now may be in some way determined by something that happened sometime in the past, and that may not be in ... |
H: How can I use a string as input in a neural network?
I'm making a program that can determine if a user will like a car from different auctions based on the cars that he/she has bought in the past. Therefore, I want to use the make and model (which are represented as strings) as well as the year, mileage etc... but ... |
H: Resume Parsing - extracting skills from resume using Machine Learning
I am trying to extract a skill set of an employee from his/her resume. I have resumes stored as plain text in Database. I do not have predefined skills in this case. How should I approach this problem?
I can think of two ways:
Using unsupervised... |
H: getting error while installing install_tensorflow()
i am trying to install tensorflow in r library. when i try to install using
> library(tensorflow)
> install_tensorflow()
Preparing for installation (updating pip if necessary)
Requirement already up-to-date: pip in c:\users\ideapad\appdata\local\programs\python\py... |
H: Gradient descent multidimensional linear regression - does learning rate affects concurrency?
I wonder if gradient descent for multidimensional regression always finds the right result? I feel like this doesn't always have to be true. I have done some calculations and actually got correct results but not for all le... |
H: Differentiating roadmap of a loss function
Let's say I'm performing Stochastic Gradient Descent (SGD) on binary cross entropy error while optimizing weight $w_{2}$.
Binary cross entropy error:
$$L(y|p(x_{i}))=-y_{i}*ln(p(x_{i}))-(1-y_{i})*ln(1-p(x_{i}))$$
The derivative of such roadmap would be:
$$\frac{\partial L... |
H: Effect of NOT changing filter weights of CNN during backprop
What is the effect of NOT changing filter weights of a CNN during backpropagation? I changed only the fully connected layer weights while training on the MNIST dataset and still achieved almost 99 percent accuracy.
AI: By not changing the weights of the c... |
H: Is there any logic to adding a threshold to see if two variables are related?
I have two variables $X$ and $Y$ given as tuples of $(x, y)$, and I want to see if there is a relationship between the two variables. I can do so by finding the correlation coefficient.
However, I found that by selecting an arbitrary subs... |
H: Missing value in continuous variable: Indicator variable vs. Indicator value
Most data has missing values, and as far as I'm aware, these are the options:
Imputation (mean, hot-deck, etc.)
Indicator variable. A categorical variable that tells what type the primary variable is. For the missing value case, this is b... |
H: converting column from a factor to date format YYYY-MM-DDThh:mm:ss.SSSZ
i want to convert the whole column from a factor to date.
The str of the dataset I am using is given below:
> str(dataset)
'data.frame': 2538 obs. of 5 variables:
$ X : int 1 2 3 4 5 6 7 8 9 10 ...
$ SessionID: int 13307 21076 278... |
H: How can I compare classes from clusterings performed on two different data sets?
I have two data sets defined by real valued vectors, and I have performed clustering on both of them. Now I want to compare the classes to see how they map to each other. If I put the data sets together into a single, bigger data set, ... |
H: Activation function vs Squashing function
This may seem like a very simple and obvious question, but I haven't actually been able to find a direct answer.
Today, in a video explaining deep neural networks, I came across the term Squashing function. This is a term that I have never heard or used. Our professor alway... |
H: Implementation of a distributed data mining paper
I have a project about distributed data mining and I need to do some implementations, So I've searched and found this paper. The address of dataset is mentioned in the paper and I've downloaded it. For the process I should split the dataset into 10 smaller datasets.... |
H: Understanding the Shuffle and Split Process in a Neural Network Code
I need to understand how the splitting of labels in the following code happened :
import keras
import librosa
import librosa.feature
import librosa.display
import glob
import numpy as np
from keras.models import Sequential
from keras.layers im... |
H: Gumbel Softmax vs Vanilla Softmax for GAN training
When training a GAN for text generation, i have seen many people feeding the gumbel-softmax from the generator output and feed into the discriminator. This is to bypass the problem of having to sample from the softmax which is a non-differentiable process and hence... |
H: Mixture Density Network: determine the parameters of each Gaussian component
I am reading Bishop's Mixture Density Network paper at:
https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/bishop-ncrg-94-004.pdf
This is a good paper, but I am still confused about a few small details. I am wondering if a... |
H: Orange wont allow me to set target for corpus
I would like to do a linear regression on an excel file. I have descriptions in one column and category in the other.
I need to be able to set the target to do a linear regression. However, Orange does not allow me to set target variable the way it would when I use the ... |
H: Is there an implementation of pocket algorithm in Keras?
As explained in Wikipedia, the pocket algorithm is a very simple variant/addition of/to ANN which keeps a copy of the best model seen so far and returns that one as the trained model (instead of the actual final state of the model). Implementing it is very si... |
H: Semi Supervised Learning without label propagation
I am trying to cluster some words by affinity.
Using Word2Vec I obtained vector representation of every word that I can cluster with a normal unsupervised method.
Of these words, though, I know the classification of some of them, for example I know:
Colors group ==... |
H: Are view() in Pytorch and reshape() in Numpy similar?
Are view() in torch and reshape() in Numpy similar?
view() is applied on torch tensors to change their shape and reshape() is a numpy function to change shape of ndarrays.
AI: Yes, for most intents and purposes, they can do the same job. From this link, an examp... |
H: What is max aggregation on a set of word embeddings?
In a paper I see:
$\mathcal{Q}$ is a set of words.
$\psi_{G^w}$ are word embeddings.
so, $\{\psi_{G^w}(w_t), \forall w_t \in \mathcal{Q}\}$ gives me a set of embeddings for all words in $\mathcal{Q}$.
For example, if I have:
Q = {'a', 'b', 'c'}
embedding_gw.sh... |
H: (Newbie) Decision Tree Randomness
I'm starting at Data Science and, to get something going, I just ran the code from Siraj Raval's Intro to Data Science video. He implements a simple Decision Tree Classifier but I couldn't help but notice that, given the same training set, the classifier doesn't always yield the sa... |
H: Why this model does not converge in keras?
This case has an underlying story but I have essentially boiled it down to the simplest possible re-producible example I could.
Essentially let us think that I have up to 1000 nodes and each node represented by a small (this case is a 3-cell vector) vector and I concatenat... |
H: lengthy criteria in dataframe selector
I'd like to get records with country codes not in a long list , something along the lines of
country_list = ['BR','MX','CO',...]
df = df[df['country_code'] not in country_list]
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or ... |
H: Multi target classification
I am working on traffic violation data set which contains 36 columns(variable). I have two dependent variables out of this.
Example
id, description, age, sex alcohol vehicle violation level Accident
120 speed 28 M Yes car severe yes ... |
H: Does MLPClassifier (sklearn) support different activations for different layers?
According to the documentation, it says the 'activation' argument specifies:
"Activation function for the hidden layer"
Does that mean that you cannot use a different activation function in different layers?
AI: One can see from the... |
H: How does ML algorithms treat unseen data, a conceptual discussion
I want to predict the occurrence of certain events, but these events only occur say 5% of the time in my data, hence in 95% of the data there is nothing to learn.
In order to teach the ML algo something I have learned to single out the 5% and drop t... |
H: How to make it possible for a neural network to tune its own hyper parameters?
I am curious about what would happen to hyperparameters when they would be set by a neural network itself or by creating a neural network that encapsulates and influences the hyperparameters of the network it encapsulates.
The goal for m... |
H: Under what circumstance is lemmatization not an advisble step when working with text data?
Disregarding possible computational restraints, are there general applications where lemmatization would be a counterproductive step when analyzing text data?
For example, would lemmatization be something that is not done whe... |
H: How to utilize user survey answers and the actual usage in forecasting power usage using LSTM?
I have the pre-trial survey and post-trial survey conducted of around 5000 users for Smart Meter installation.
With this I have power usage reading recorded every 30 min for around one and a half years.
survey csv is like... |
H: How to do face recognition without using any kind of Neural Networks like CNN?
Is/was there any way to perform face recognition, instead of using the Convolution Neural Network which uses the technique of mapping(encoding) the face using 128-D vector and then using classifier (like knn/SVM) on it?
Before the invent... |
H: May the training set and validation set overlap?
May the training set and validation set overlap?
Similarly, may the testing set and validation set overlap?
AI: Definitions, so we are on the same page:
Training set: the data points used to train the model.
Validation set: the data points to keep checking the perfo... |
H: sklearn nmf - question about its use
This is a complete noob question, I'm new to Python, and I understand the basics of NMF, but when implementing it in sklearn it seems a bit convoluted and I wanted to ask whether anyone knows how to exploit the results.
I've imported data from a file, and created and shaped an ... |
H: Why are optimization algorithms slower at critical points?
I just found the animation below from Alec Radford's presentation:
As visible, all algorithms are considerably slowed down at saddle point (where derivative is 0) and quicken up once they get out of it. Regular SGD itself is simply stuck at the saddle poin... |
H: is numpy isclose function returning bad answer?
Using numpy isclose in the following example:
import numpy as np
np.isclose(1533761040,1533748023.0, atol=1)
Returns True, which is False.
AI: No, it uses both an absolute and relative tolerance, and the default of rtol is nonzero, adding some more tolerance. See htt... |
H: Why use two LSTM layers one after another?
In the example on the Keras site, seq2seq_translate.py on line 189, there is a LSTM layer after another (the first with return_sequences=True), but another example lstm_seq2seq.py which does the same thing but letter-by-letter uses only one LSTM in the encoder. My code loo... |
H: In RNNs why do networks always use the last output vs the last input?
All the descriptions of RNNs introduce some equation like:
$\ h_t = f_W(h_{t-1},x_t)$
and I'm wondering why we don't just go straight to the "source", ie the last input like :
$\ h_t = f_W(x_{t-1},x_t)$
The only thing I can maybe think of is ma... |
H: Is regularization included in loss history Keras returns?
I'm getting to know Keras. Right now, I'm testing with regularization and how to use them. Comparing the results of loss history for a training session with and without regularization, it seems to me that the loss history reported by Keras has the regulariza... |
H: Macro- or micro-average for imbalanced class problems
The question of whether to use macro- or micro-averages when the data is imbalanced comes up all the time.
Some googling shows that many bloggers tend to say that micro-average is the preferred way to go, e.g.:
Micro-average is preferable if there is a class im... |
H: How to add confidence to model's prediction?
I am a newbie in ML working on a time series prediction project. The objective is to predict the future outcome of a time series (int valued, with different upper bound, think of it as different sized parking lot availability prediction) based on its historical value.
I'... |
H: How to display the value of activation?
I have built my network and would like to see how the activation of a particular layer change after each epoch of training. For example, as code shown below, I want to see the activation values of "act_layer_1". What should I do so that I can see the activation values? Thanks... |
H: What does it mean by “t-SNE retains the structure of the data”?
I was learning about t-SNE when I was told that t-SNE retains the structure of the data in the embeddings.
What exactly does this mean ?
How does the algorithm achieve this ?
So far I have understood this ->
t-SNE is an unsupervised learning algorithm ... |
H: Dataframe looks the same but the structure is different when loop
I am generating a dataframe from a JSON file, this JSON file can come from 2 different sources, so the internal structure is slightly different, so what I am doing is first detecting the source and from there I do a set of operations that gives me a ... |
H: Hindsight Experience Replay: what the reward w.r.t. to sample goal means
Referring to the paper on Hindsight Experience Replay
Is it right that sampled goals which are visited states should be followed by a positive (or non-negative) rewards in order to allow an agent learn?
On page 5 of the paper, a "Algorithm 1 H... |
H: Decision tree where identical set of features results in different outcomes
I am following the example described in this page to test my decision tree program.
The initial data set is
age astigmatism, tp-rate, contact-lenses
---------------------------------------------------
young, no, norma... |
H: Please explain input shape in Keras
My data consists of 2-dimensional arrays with shape (2,3).
The whole dataset (emp) consists of 12 items (I know that it is too small of a number for an NN training, but it is just a test), so it has shape (12,2,3)
truevals has shape (12,)
When I try to add Keras layer:
model = Se... |
H: how to save deep learning model and test it after training?
I have a CNN model written using tensorflow for python, the model is for classifying lung CT images (cancer/no-cancer), after training the model with training and validation data and get a reasonable accuracy, after all, that I need to test the model with ... |
H: Interpreting the Root Mean Squared Error (RMSE)!
I read all about pros and cons of RMSE vs. other absolute errors namely mean absolute error (MAE). See the the following references:
MAE and RMSE — Which Metric is Better?
What's the bottom line? How to compare models
Or this nice blogpost, or this question in stats... |
H: Knowledge of statistics To be a data scientist
I am an undergraduate student pursuing my BSc in Maths. I have taken statistics classes in first year. I want to know how much statistics do I need to know to get a decent place in the data science world?
Also, please do provide me with suggestions where to begin if I... |
H: Adding the input layer - units with a decimal
I took the course Machine Learning A-Z from Udemy and am trying to apply what I learned in the tutorials. Theye taught us in the "Adding the input layer" portion of an ANN that the units is based off of the input_dim. Normally the "units = (input_dim + 1) / 2". In th... |
H: CNN to learn and visualize 2d features
In the paper Large-Margin Softmax Loss for Convolutional Neural Networks the author has a figure as below:
He is claiming that he is using only 2d features to classify MNIST with a CNN. How is he doing that? Is he reducing the dimension of MNIST images to 2 and how? How do yo... |
H: Why does adding a dropout layer improve deep/machine learning performance, given that dropout suppresses some neurons from the model?
If removing some neurons results in a better performing model, why not use a simpler neural network with fewer layers and fewer neurons in the first place? Why build a bigger, more c... |
H: NLP - How to perform semantic analysis?
I'd like to perform a textual/sentiment analysis.
I was able to analyse samples with 3 labels: (positive, neutral, negative) and I used algorithms such as SVM, Random Forest, Logistic Regression and Gradient Boosting.
My script works correctly and with the cross validation I ... |
H: finding start and end time of each session id in r
suppose i have a dataframe
suppose i have a dataframe
> data
session id timestamp item id
1 2014-04-0618:42:05.822 1
1 2014-04-0618:42:06.800 1
1 2014-04-0618:42:06.820 1
2 2014-... |
H: CNN, which layer to choose for a similarity measure
I built a model (InceptionResnet v2) to classify images and I would like to use it to measure similarity between objects.
One way to measure that similarity is to catch an intermediate layer's results from two vector and look their distance.
I don't know how to c... |
H: Keras backend function equivalent for str.format
How to perform the following function using Keras backend?
"{0:b}".format(37)
AI: Why do you need that? You shouldn't need to do anything like that using the backend, as Keras will take strings as arguments, or you can use a regular print function.
There are certain ... |
H: Topic Segmentation - should it be done in Raw, TfIdf or Semantic Space?
Let's assume we have a collection of documents and wish to perform some unsupervised topic segmentation.
As always, we will perform some preprocessing (including tokenization, accent-removal, lowercasing, lemmatizing and such) and transform the... |
H: Is it a good idea to normalize the outputs of a Neural Network for Regression, when the different outputs vary in magnitude?
I understood that it is not necessary to scale the output of a neural Network when I predict a single value via regression.
Is it necessary do normalize the Outputs of my neural Network if I ... |
H: Logistic Regression or regression SVM for probability of outcome
I am working on a prediction question: what's the percentage of Y = 1 using a number of features?
The output Y values I have for training are in binary. In this case, should the prediction be treated as classification or regression?
Would logistic ... |
H: calculating average of each session by unique itemID
i have a data frame
> data
session id item id
1 1
1 1
1 1
2 1
2 2
3 1
3 0
3 3
3 2
and i w... |
H: How can ReLU ever fit the curve of x²?
As far as I understand (pardon me if I am wrong) the activation functions in a neural network go through the following transformations:
Multiplication by constants(weights) to x ( $f(ax)$ , $f(x)$ being the activation function).
Recursive substitution $f(f(x))$.
Now with the... |
H: What is wrong with this reinforcement learning environment ?
I'm working on below reinforcement learning problem:
I have bottle of fix capacity (say 5 liters). At the bottom of bottle there is cock to remove
water. The distribution of removal of water is not fixed. we can remove any amount of water from bottle, i.e... |
H: How to auto tag texts
Suppose we have predefined list of tags Tag #1, Tag #2, ..., Tag #N
and we want to assign tags to sample texts based on keywords or semantic analysis. A text can have multiple Tags. I don't want to consider it as classification problem assuming each tag as a separate class. What algorithm we c... |
H: Predicting Composition of Chemical Compounds
I have a dataset which has names of compounds and their compositions. Like below
Sulphuric Acid=>[H,S,O] (Hydrogen, sulphur, oxygen)
Oxalic Acid=>[H,C,O]
Sodium Oxalate=>[Na,C,O]
Potassium Sulphate=>[K,S,O]
...
Now I would need to train a model which can tell me Sodium S... |
H: K-fold crossvalidation: how do MSE average and variance vary with K?
I'd like to get an intuition about how varying k impacts k-fold validation.
Is the following right?
Average of the OOS MSEs should generally decrease with k
Because, a bigger "k" means the training sets are larger, so we have more data to fit th... |
H: How to use Cross Entropy loss in pytorch for binary prediction?
In the pytorch docs, it says for cross entropy loss:
input has to be a Tensor of size (minibatch, C)
Does this mean that for binary (0,1) prediction, the input must be converted into an (N,2) tensor where the second dimension is equal to (1-p)?
So fo... |
H: When memory errors occur with model.fit(), is it due to GPU RAM or normal RAM?
With respect to this question,
https://stackoverflow.com/questions/51895278/how-to-know-when-to-use-fit-generator-in-keras-when-training-data-gets-too-big
when memory errors are reported due to excessively large training data, are the m... |
H: High RMSE and MAE and low MAPE
I have used a few regression models on the same dataset and obtained error metrics for them as shown below,
The RMSE(Root Mean Squared Error) and MAE(Mean Absolute Error) for model A is lower than that of model B where the R2 score is higher in model A. According to my knowledge this... |
H: splitting of training examples into the mini batch: what to do with the rest tiny mini-batch?
Lets assume I have 103 training examples. I want a mini-batch to be of the size 16. That means that there will be 6 mini-batches of the size 16 and one mini-batch of the size 7.
In the tensor flow one needs to specify the ... |
H: How does action get selected in a Policy Gradient Method?
As I understood, in Reinforcement-Learning a big difference between a Value-based method and a Policy-gradient method is how the next action is selected.
In Q-learning (Value-based method), each possible action gets a score. We then select next action that h... |
H: Poker tournament winner prediction
I am trying to solve poker tournament winner prediction problem. I’ve millions of historical records in this format:
Players ==> Winner
P1,P2,P4,P8 ==> P2
P4,P7,P6 ==> P4
P6,P3,P2,P1 ==> P1
I want to find the best algorithm to predict winner from set of known players.
So far ... |
H: Understanding data normalisation
So I know that when we have different parameters with different value ranges we have to standardise these values. Also, I read that when a parameter does in fact require higher values then we should not normalise it. However, isn't this always the case? For example, if we have age a... |
H: How to remove rows from a dataframe that are identical to another dataframe?
I have two data frames df1 and df2.
For my analysis, I need to remove rows from df1 that have identical column values (Email) in df2?
>>df1
First Last Email
0 Adam Smith email@email.com
1 John Brown email2@email.com
2 Joe Max... |
H: Why convolution over volume sums up across channels?
A simple question about convolution over volume .
Say we have an image with dimensions $(n, n, 3)$ and we apply a filter of dimension $(k, k, 3)$ this outputs an matrix of dimension $(n-k+1, n-k+1)$.
Why do we sum across channels in this case. Don't we lose info... |
H: Orange Data Mining load saved models
I am planning to use the Orange Data Mining Tool for easy data exploration and model generation. What is still unclear to me is: after finding a good model, what can I do with it, how can I use or deploy it in production?
I already found out that there is no Orange server which ... |
H: Combining outputs of ridge regression models?
I am facing an issue where I have 7 sets of different variables/columns/predictors.
I am trying to predict same target variable and I want to observe the importance/effect of all the sets according to their importance in an ordered manner. (I am trying to use ridge regr... |
H: Why would a validation set wear out slower than a test set?
On this page of Google's Machine Learning Crash Course, we find the following statement:
"Test sets and validation sets "wear out" with repeated use. That is, the more you use the same data to make decisions about hyperparameter settings or other model im... |
H: Which type of clustering algorithm to use to identify the "same" item in different data sets?
I'm trying to find a solution for a data quality problem - specifically, identifying which items in different data sets are used to represent the same things.
As an example, assume that we're a retailer and we buy out a co... |
H: What is the meaning of term Variance in Machine Learning Model?
I am familiar with terms high bias and high variance and their effect on the model.
Basically your model has high variance when it is too complex and sensitive too even outliers.
But recently I was asked the meaning of term Variance in machine learning... |
H: Unblanced classes: classifier only predict one class
I am trying to use a multiclass classification using python. For that I used few algorthims like Random Forest, Xgboost, Logitic regression.
My problem is simple, I have users, Images, and people ratings on those images. I devided the ratings into 3 classes:
cla... |
H: Why is the softmax function often used as activation function of output layer in classification neural networks?
What special characteristics of the softmax function makes it a favourite choice as activation function in output layer of classification neural networks?
AI: The softmax function is simply a generalisat... |
H: When should one use L1, L2 regularization instead of dropout layer, given that both serve same purpose of reducing overfitting?
In Keras, there are 2 methods to reduce over-fitting. L1,L2 regularization or dropout layer.
What are some situations to use L1,L2 regularization instead of dropout layer? What are some si... |
H: Character Level Embeddings
I am working on a problem that current depends on word level embeddings created using Word2Vec. I am researching new methods to apply to this model and one was a character level embedding. I have not found much information on it, and I don't imagine Word2Vec but at a character level would... |
H: What are kernel initializers and what is their significance?
I was looking at code and found this:
model.add(Dense(13, input_dim=13, kernel_initializer='normal', activation='relu'))
I was keen to know about kernel_initializer but wasn't able to understand it's significance?
AI: The neural network needs to start wi... |
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