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H: Finding parameters of image filter using classified pairs
I want to solve the problem of finding a parameter vector for an image filter (let us assume we know nothing about how the filter works, but we can feed it an input image and a set of parameters to produce an output image).
Thus, having a set $\{{I_k, J_k:=F... |
H: Data dashboard for SQL server database
I am working on developing a data dashboard / app for a Microsoft SQL database. Currently, I am developing the dashboard using Shiny and R. The app is mostly for exploratory analysis to allow people to filter out some subset of data, build some plots, and export data / plots. ... |
H: Forget Layer in a Recurrent Neural Network (RNN) -
I'm trying to figure out the dimensions of each variables in an RNN in the forget layer, however, I'm not sure if I'm on the right track. The next picture and equation is from Colah's blog post "Understanding LSTM Networks":
where:
$x_t$ is input of size $m*1$ ve... |
H: Neo4j graph to cypher conversion
Is there a way or tools available to generate or retrieve cypher query from a Neo4j database ? Should we need to store cypher quries along with the graph data for regeneration ?
AI: This has already been answered in stackoverflow. There is no need to save the queries you used to pop... |
H: Tensorflow ArgumentError: argument --model_dir: conflicting option string: --model_dir
I am trying to execute this Tensorflow tutorial https://github.com/tensorflow/tensorflow/blob/r0.12/tensorflow/examples/learn/wide_n_deep_tutorial.py but I have the following error:
ArgumentError: argument --model_dir: conflictin... |
H: Detecting anomalies with neural network
I have a large multi dimensional dataset that is generated each day.
What would be a good approach to detect any kind of 'anomaly' as compared with previous days? Is this a suitable problem that could be addressed with neural networks?
Any suggestions are appreciated.
Additio... |
H: Why do we use +1 and -1 for marginal decision boundaries in SVM
While using support vector machines (SVM), we encounter 3 types of lines (for a 2D case). One is the decision boundary and the other 2 are margins:
Why do we use $+1$ and $-1$ as the values after the $=$ sign while writing the equations for the SVM ma... |
H: Predict sinus with keras feed forward neural network
I have a very simple feed forward neural network with keras that should learn a sinus. Why is the predictive power so bad and what is generally the best way to pinpoint issues with a network?
In the code below, I have one input neuron, 10 in the hidden layer, and... |
H: Why my loss is negative while training SAE?
I am using loss='binary_crossentropy' here is my code:
I tried to increase number of training image and Epoch ,but that did not help me.
input_img = Input(shape=(28, 28, 1))
x = Convolution2D(16, 3, 3, activation='relu', border_mode='same')(input_img)
x = MaxPooling2D((2... |
H: Propensity Modeling, still use Test/Train Split?
I'm using Sklearn to build a classifier in which my client wants a predicted probability for each row of data. The default of let's say Random Forest is if > 50%, then classifies as TRUE, but using the predict_proba function I'm able to get the probability.
The data... |
H: Keras: Built-In Multi-Layer Shortcut
Problem
In Keras for Python, I have to use multiple lines of code for a simple XOR neural network:
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD
import numpy as np
X = np.array([[0,0],[0,1],[1,0],[... |
H: Neural Networks for time series
I have an understanding problem. I am a beginner in machine learning and have also a little experience in modelling NNs but not for time series.
But I cannot imagine how to use Neiural Networks for time series.
So if I want to train a Multilayer NN what is the input?
I read several ... |
H: Word2Vec Alternative for Smaller Datasets
I am looking to employ Word2Vec to cluster documents and classify them by topic. However, it seems I need a significant data set [1,2] to achieve such a task.
I have a data set of thousands (not millions) of documents where my total word count is somewhere in the tens of ... |
H: Is Stratification applicable to both Classification and Regression?
It is usually better if you have a not so large but balanced dataset and you are performing classification to apply stratification in order to split it in a training and testing datasets which are both balanced as well.
So there is a notion of havi... |
H: How is the salary for Data Scientist different among countries?
I would like to know the salary for Data Scientists by countries, but failed to find any resources on it.
I know that US gives data scientists an insanely high amoung of money (well, it might not be "insanely high" on the standard of US), but I rarely ... |
H: How to determine the complexity of an English sentence?
I am working on an app to help people learn English as a second language. I have validated that sentences help in learning a language by providing extra context. I did that by conducting a small research in a classroom of 60 students.
I have mined over hundred... |
H: AUC and classification report in Logistic regression in python
I have been trying to implement logistic regression in python. Basically the code works and it gives the accuracy of the predictive model at a level of 91% but for some reason the AUC score is 0.5 which is basically the worst possible score because it m... |
H: Question Regarding Multi-label probability predictions
I have been doing a problem in which I have to predict probabilities for each of the labels in a multi-label (four to be precise) classification problem.
Example of a solution:
Id, North, East, West, South
1, 0.71663940211, 0.037... |
H: Is it always possible for validation accuracy to be as high as training accuracy?
I have a very small dataset (40 training examples, 10 validation examples, 120 classes) for which I'm getting very high accuracies with a very simple model in Keras (batchnorm, flatten, and dense layers only).
My training accuracy is ... |
H: Extracting sub features from inside a df cell?
I have a dataframe containing several features of form:
Id, Acol, Bcol, Ccol, Dcol,
1, X:0232,Y:10332,Z:23891, E:1222, F:12912,G:1292, V:1281
2, X:432,W:2932 R:2392, T:292,U:29203 Q:2392
3, Y:29320,W:2392 R:2932, G... |
H: Learning character embeddings with GenSim
I am learning deep learning, and as a first exercise to myself I am trying to build a system that learns a very simple task - capitalize the first letter of each word. As a first step, I am tried to create "character embeddings" - a vector for each character. I am using th... |
H: Is it possible to change misclassification cost in caret?
0
down vote
favorite
I have an imbalanced dataset to work with (with about 20-fold positive examples than negative). I know several solutions to deal with this type of data (under/oversampling, optimizing for AUC, etc.) but I would like to try changing the m... |
H: Standard method to integrate tools coded in multiple languages in an analysis workflow
I am trying to stitch together multiple packages and tools from multiple languages (R, python, C etc.) in a single analysis workflow.
Is there any standard way to do it? Preferably (but not necessarily) in python.
AI: Luigi is an... |
H: What are the "extra nodes" in XGboost?
When training an XGboost model some of the information printed regards "extra nodes". I can't find an explanation of these anywhere in the documentation. What exactly are extra nodes?
[14:13:09] C:\dev\libs\xgboost\src\tree\updater_prune.cc:74: tree pruning end, 1 roots, 54 ex... |
H: Recommender system based on purchase history, not ratings
I'm exploring options for recommender systems optimized for the insurance industry, which would take into account
i) product holdings
ii) user characteristics (segment, age, affluence, etc.).
I want to stress that
a) there are no product ratings available, t... |
H: ICD-10 codes in Machine Learning
Can anyone provide specific techniques with using ICD-10 codes in Machine Learning? I have usually used a simply approach of creating multiple binary column representing ICD-10 codes… which can get extremely long. Or I have used Hashing features. Are there other techniques or ways t... |
H: How do you calculate sample difference in terms of sensor signals?
A paper I read called Preprocessing Techniques for Context Recognition from Accelerometer Data refers to sample difference as the delta value between signals in a pairwise arrangement of samples that allows a basic comparison between the intensity ... |
H: Merge two models - Keras
I was reading through many blogs and understood the relevance and scenario of having merging two model. But, how to decide the Merge mode for two models. ie. concat, sum, dot, etc.
For eg. I am working on the task of Auto Image captioning. So, captions and Images are 2 kinds of input that I... |
H: Difference between rand index and adjusted rand index?
I am unable to understand what is the adjusted term in ARI. The expected index term in the ARI is from a prior. Kindly explain
AI: The adjustment is simply
(Rand index - Expected value)/(Optimal value - Expected value)
The purpose is to scale it in an interpret... |
H: Is pre-processing always neccessary?
I'm working on classification of two classes of Raman spectra. And while I was working on finding the optimal steps for pre-processing, I started to wonder if it is really necessary.
I have a lot of Raman spectra data and and most of them differ between both classes even to the ... |
H: Sequence Batching in RNNs
I'm wondering why sequence batching in RNNs's target value loops back (I'm not sure what you call it), but let's take for example:
We want to learn a sequence of numbers (our input) from 1 to 16:
$$
\begin{bmatrix}
1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 & 13 & 14 ... |
H: Why my training and validation loss is not changing?
I used MSE loss function, SGD optimization:
xtrain = data.reshape(21168, 21, 21, 21,1)
inp = Input(shape=(21, 21, 21,1))
x = Conv3D(filters=512, kernel_size=(3, 3, 3), activation='relu',padding='same')(inp)
x = MaxPool3D(pool_size=(3, 3, 3),padding='same')(x)... |
H: Linear Regression and k-fold cross validation
I am totally new to the topic of Data Science. With the help of the following sources, I think I have managed to do a very simple and basic Linear regression on a train dataset:
SkLearn documentation - Linear regression
Some Kernel, that I percieved as intuitive
the te... |
H: Tool for analyzing a Python matrix and generating a report on the contents (column types, NaN counts, means, etc.)
I'm looking for a tool/library that will take a numpy or pandas matrix and generate a list of statistics for the matrix and columns. Specifically, for each column, I'd want info like the following:
As... |
H: Determining Statistically Significant Differences in Views per Day of Week?
I have some views per day of week data. It's something like:
Mondays: 100k views
Tuesday: 110k views
Wednesday: 140k views
...
Sunday: 80k views
So naively, it seems like Wednesday is a better day for website traffic. However, I also unde... |
H: Depth of the first pooling layer outcome in tensorflow documentation
Let's say that we have a CNN with two convolutional layers (https://www.tensorflow.org/tutorials/layers). My question regards the dimension of the tensor, which is the output of the pooling layer 1.
In the first convolutional layer, we apply $32$ ... |
H: Find average sequence from a set of sequences
I have a set of user sessions. Session consists of an ordered list of types of actions that user made (for example, bought a gun, played a mission, etc).
I want to create/calculate session that have most possible similarity to all provided sessions (most common types of... |
H: How to visualize multi-instance multiclass classification?
Let's say I have 3 classes and 1 score for each data point
score z
class 1
class 2
class 3
E.g. the input looks like:
0.529 5 7 4
0.310 3 4 2
0.774 10 7 6
0.774 10 8 5
0.172 3 0 2
In code:
>>> import pandas as pd
>>> df = pd.DataFrame([[0.529, 5.0, 7.0, ... |
H: What is PCA and MICE
I am doing an experiment on Azure ML. While pre processing my data, there is an option to clean missing data using either PCA or MICE.
Please provide me an example of how I can decide on which option to choose.
AI: I don't know about Azure ML. But:
PCA is principal components analysis. It tak... |
H: Clustering a very large number of very small clusters with most data unrelated
I'm trying to detect duplicates in a data set of about 34k distinct items. When I say "duplicate," I don't mean identical items, just very similar. I have an algorithm that will Cartesian join the items and return a sparse matrix of simi... |
H: How to more simply see overlapping data for dozens of variables?
I'm trying to think of the best way to see how multiple variables (about 40) related to a very large userbase can be seen to interact with one another.
As an analogy, imagine I had survey data of superheros liked by thousands of school children, such ... |
H: How to choose validation set for production environment?
I am using XGBoost for a time-series regression problem.
During development, i choose my validation set on last %10 percentage of data. Using timeseries split cross validation and grid-search, I got my best model on this with corresponding xgb hyperparameters... |
H: Range to define emotions
We are capturing emotions as survey responses. We need to assign values for the responses(emotions) for analysis purposes. Is there an optimum range that can be assigned to achieve this? (like from -100 to 100). An example of a question and a set of answers are as follow.
Question: "How ar... |
H: How predictions of level 1 models become training set of a new model in stacked generalization.
In stacked generalization, if I understood well, we divide the training set into train/test set. We use train set to train M models, and make predictions on test set. Then we use the predictions as input of a new model. ... |
H: How to change a cell in Pandas dataframe with respective frequency of the cell in respective column
I have a pandas dataframe with binary value columns. I would like to replace values in each cell with its frequency in rspective column in place. My question is how to keep track of the current column while using app... |
H: How to score arbitrary sentences based on how likely they are to occur in the real world?
According to article about LSTM here, I know that:
it allows us to score arbitrary sentences based on how likely they are to occur in the real world. This gives us a measure of grammatical and semantic correctness. Such model... |
H: Time series forecast using SVM?
I have a pandas data frame like this:
(index) 0 sie
0 1997-01-01 11.2
1 1997-01-03 12.3
2 1997-01-04 11.5
...
12454 2017-02-01 13.2
I would like to use SVM to predict the future values of the sie. How can I implement python code to predict these... |
H: How can I have an "undefined" category in multi-class classification
I'm trying to classify several websites by category (finance, health-care, IT, etc...). I have at my disposal the content of the pages of the websites, and I use the words to classify. For now, I have manually classified some website to train a na... |
H: Explain output of logistic classifier
[Note : There is some serious problem with logic used to get the best banner. I got it late. Directly read the answer to get general info, or you can also try to the find the mistake.]
Problem: Given a set of user features, select an ad with the highest probability to be clic... |
H: Is Gini coefficient a good metric for measuring predictive model performance on highly imbalanced data
I am evaluating a Credit Risk model that predicts the estimated likelihood of customers defaulting on their mortgage accounts. The model is a Logistic Regression estimator and was built by another team. They use t... |
H: How to implement Python's MLPClassifier with gridsearchCV?
I am trying to implement Python's MLPClassifier with 10 fold cross-validation using gridsearchCV function. Here is a chunk of my code:
parameters={
'learning_rate': ["constant", "invscaling", "adaptive"],
'hidden_layer_sizes': [(100,1), (100,2), (100,3)],
'... |
H: Why does gradient descent gives me much better Relative Squared Error then the Least Squares approach?
Am I doing regression task with 7 dependent variables and 10000 data points. The SGD gives me 22% of mean absolute percentage error on test and train dataset. And Least Squares method using numpy scipy.optimize.le... |
H: Categorical Variables - Classification
I have a categorical variable, country which takes on values like India, US, Pakistan etc. I am currently using a linear SLM for a classification task.
So my country value varies from 1-20. How should this be a feature in the classification task. Should i have a one hot vector... |
H: is there any way to plot ROC curves from weka
i am using some algorithms from weka . i was willing to plot some algorithms' roc curve for comparison . Is it possible and how ?
AI: In the Weka explorer, go to the classify tab and train/test your algorithm.
The result buffer appears in the bottom left box under the s... |
H: Why some people add results from PCA and other dimensional reductions techniques as features
I often see in a well-known datascience competition platform, that a lot of people apply some dimension reductions techniques, but instead of using it to reduce the number of features (complexity) of their models, they appe... |
H: Is it good to remove outliers from the dataset?
Suppose you have some training dataset that you want to use to train some ML models, where targets are comprised between let's say 1 and 100. However, from the 4000 samples, there are few of them (less than 10) which have values out of the previous range, much higher ... |
H: Evaluating Logistic Regression Model in Tensorflow
Following this tutorial, I have a doubt about the evaluation part in:
# test the model
n_batches = int(mnist.test.num_examples/batch_size)
total_correct_preds = 0
for i in range(n_batches):
X_batch, Y_batch = mnist.test.next_batch(batch_size)
_, loss_batch,... |
H: How to transform raw data to fixed-frequency time series?
How to transform raw data to fixed-frequency time series?
For example I have the following raw data in DataFrame
A B
2017-01-01 00:01:01 0 100
2017-01-01 00:01:10 1 200
2017-01-01 00:01:16 2 300
2017-01-01 00:02:35... |
H: Best Programming Language for Data Science
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 for processing data?
P.S. I love statistics and programming so I think this... |
H: why is the model prediction output in keras lstm imdb, a vector?
If you run the example of the LSTM sentiment classification task example in keras
https://github.com/fchollet/keras/blob/master/examples/imdb_lstm.py
and add
p = model.predict(x_test[0])
print(p.shape)
you get:
(80,1)
.. why? I thought the point of... |
H: Feature Normalization/Scaling: Prediction Step
I'm just doing a simple linear regression with gradient descent in the multivariate case. Feature normalization/scaling is a standard pre-processing step in this situation, so I take my original feature matrix $X$, organized with features in columns and samples in rows... |
H: How to further Interpret Variable Importance?
Forgive me if this is a duplicate question, I haven't found anything that answers my question specifically after searching for a while.
I have a dataset which I'm using to predict mobile app user retention, using the RandomForestClassifier in the SciKit Learn package. I... |
H: Does increasing the n_estimators parameter in decision trees always increase accuracy
I'm using some ML algorithms (from sklearn lib) and on most of them there is a parameter n_estimators which is (if I understood well) the number of used trees. Intuitevely I would say that the more trees you use, the more accurate... |
H: Xgboost - How to use feature_importances_ with XGBRegressor()?
How could we get feature_importances when we are performing regression with XGBRegressor()?
There is something like XGBClassifier().feature_importances_?
AI: Finally I have solved this issue by:
model.booster().get_score(importance_type='weight') |
H: What kind of algorithms can be used as a stacker in stacked generalization?
In stacked generalization, several algorithms (I use some random trees, booster trees, etc.) are first trained and used to make the predictions which are used as input for another algorithm. However, can I use any kind of algorithms, or is ... |
H: How can I deal with data that is on the format "Image + single number"?
Let say I have a data set where every sample is an image of a landscape and a temperature associated with the landscape. How do I incorporate the temperature into my convolutional neural network for classifying if the data is e.g a winter or su... |
H: Cluster documents based on topic similarity
I have set of documents where I have assigned topics per each document.
E.g., Topics of document 1 -> 1.0 Science, 1.0 politics, 0.8 History, 0. 8 Information and Technology
Now I want to cluster these documents and find what are the documents that share similar like topi... |
H: How to measure the correlation of different algorithms
In stacked generalization, several algorithms are trained on the training set (i.e. at layer 1) and their predictions are then stacked using a layer 2 model. In many documentations, it is said that it is better that the layer 1 algorithms should be of low corre... |
H: Using simulations to train ML algorithms
Possibly similar question: Is it ok to collect data using algorithm to train another?
I have a model that accurately describes an underlying physical, complex, system. The model is basically a set of ODEs based on the physics of the system, validated against measurements. Wh... |
H: Techniques to clean the topics
I have set of topics as follows.
"web based", "web-based" -> with surplus symbols
"technology","technologies" -> with singular and plural
"learned", "learnt", "learning" ->suffix stripping
Can you please recommend an accurate tool to perform aforementioned tasks.
AI: For text processi... |
H: Encoding Time Values
I am using Python/Scikit to do data encoding before I go ahead and train my Neural Network. I have a few columns that look like this
07:05:00
08:41:00
17:25:00
12:58:00
08:56:00
11:59:00
17:25:00
15:24:00
Any suggestions on how to encode this? Or is leaving it like this fine?
AI: I have decid... |
H: Word2Vec vs. Sentence2Vec vs. Doc2Vec
I recently came across the terms Word2Vec, Sentence2Vec and Doc2Vec and kind of confused as I am new to vector semantics. Can someone please elaborate the differences in these methods in simple words. What are the most suitable tasks for each method?
AI: Well the names are pret... |
H: How do I load FastText pretrained model with Gensim?
I tried to load fastText pretrained model from here Fasttext model. I am using wiki.simple.en
from gensim.models.keyedvectors import KeyedVectors
word_vectors = KeyedVectors.load_word2vec_format('wiki.simple.bin', binary=True)
But, it shows the following errors... |
H: Schema matching using machine learning
I'm facing the following problem of integrating data from another company (data base) to an internal one. It's about personal core data, i.e. name address etc. I would like to come up with a mapping of these keys in an automated way. I've read about HMM to use for this. Howev... |
H: Clustering algorithms
I have sparse vectors and found that cosine similarity is very efficient to to measure the similarity. Now I want to cluster these vectors based on similarity. Hence, can someone please suggest/recommend clustering algorithms that make use of cosine similarity?
P.S.: I do not have a predefined... |
H: Is it better to have binary features rather than class ones
I have a dataset containing several features, which have class values (e.g. DBF4, JUL23, ...). In a classification problem and when using decision trees, is it better to convert these values as new binary features: so DBF4 will become a feature, which valu... |
H: Advantages of pandas dataframe to regular relational database
In Data Science, many seem to be using pandas dataframes as the datastore. What are the features of pandas that make it a superior datastore compared to regular relational databases like MySQL, which are used to store data in many other fields of program... |
H: Gradients for bias terms in backpropagation
I was trying to implement neural network from scratch to understand the maths behind it. My problem is completely related to backpropagation when we take derivative with respect to bias) and I derived all the equations used in backpropagation. Now every equation is match... |
H: MOOCs for Python in Data Science
Thanks also to SE, I've recently changed job and now I'm working in Data Science, mainly on Analytics for the IoT (Internet of Things). Analytics are applications on cloud platforms which collect real-time, streaming sensor data from industrial machines and allow to estimate their a... |
H: How to check if sentiment analysis is required?
I have a CSV file having a bunch of sentences related to science. Before I do sentiment analysis on the sentences I want to programatically decide whether sentiment analysis is required on the sentence or not.
Basically some of the sentences are opinions of a particul... |
H: Issues with NLTK lemmatizer (WordNet)
I want to lemmatize set of plural keywords automatically such as 'Web based technologies', 'Information systems' etc. I want to transform them to to 'Web based technology', 'Information system' respectively.
I tried NLTK as follows
from nltk.stem import WordNetLemmatizer
lemma... |
H: neural network for binary classification of xor gate
i have written this neural network for XOR function.the output is not correct.it is not classifying the test inputs correctly.can anyone please let me the reason why.
import numpy as np
import pandas as pd
x=np.array([[0,0],[0,1],[1,0],[1,1]])
y=np.array([[0],... |
H: How do you make an NN for image classification invariant to translation **and** rotation?
CNN are (I think) invariant to small translations of the input image, i.e., they will classify to the same class an image $X$ and an image $X'$ such that all pixels have been translated along a vector $\mathbf{v}$ by some "sma... |
H: What is the advantage of keeping batch size a power of 2?
While training models in machine learning, why is it sometimes advantageous to keep the batch size to a power of 2? I thought it would be best to use a size that is the largest fit in your GPU memory / RAM.
This answer claims that for some packages, a power ... |
H: train_test_split() error: Found input variables with inconsistent numbers of samples
Fairly new to Python but building out my first RF model based on some classification data. I've converted all of the labels into int64 numerical data and loaded into X and Y as a numpy array, but I am hitting an error when I am try... |
H: Cluster documents and identify the prominent document in the cluster?
I have a set of documents as given in the example below.
doc1 = {'Science': 0.7, 'History': 0.05, 'Politics': 0.15, 'Sports': 0.1}
doc2 = {'Science': 0.3, 'History': 0.5, 'Politics': 0.1, 'Sports': 0.1}
I want to cluster the documents and identi... |
H: How to determine if my GBM model is overfitting?
Below is a simplified example of a h2o gradient boosting machine model using R's iris dataset. The model is trained to predict sepal length.
The example yields an r2 value of 0.93, which seems unrealistic. How can I assess if these are indeed realistic results or si... |
H: Should the depth on convolutional layers be set to a figure divisible by 2?
I'm reading a book titled Python Deep Learning, and in Convolutional layers in deep learning on the chapter 5, the following is written:
One more important point to make is that convolutional networks should generally have a depth equal to... |
H: How to decide neural network architecture?
I was wondering how do we have to decide how many nodes in hidden layers, and how many hidden layers to put when we build a neural network architecture.
I understand the input and output layer depends on the training set that we have but how do we decide the hidden layer a... |
H: How to use live data to improve a existing model?
I am using logistic regression to train a model to predict 'click/non-click' using ['browser info', 'publisher info', , 'location', 'time', 'day'].
I wanted to know the ways in which I can use the new live data to improve the improve the already trained model.
... |
H: How to improve my self-written Neural Network?
I created the following Neural Network in Python. It uses weights and biases which should follow standard procedure.
# Define size of the layers, as well as the learning rate alpha and the max error
inputLayerSize = 2
hiddenLayerSize = 3
outputLayerSize = 1
alpha = 0.5... |
H: Data Type required in Weka
I want to run several Association rule mining techniques such as Apriori, Eclat and FP Growth. I want to know the format of the data to run these algorithms as they are disabled (marked in grey)to me.
Also I don't see the algorithm Eclat in the 'Association' tab of Weka. Please recommend ... |
H: I trained my data and obtained a training score of 0.957. Why can't I get the data to provide a prediction even against the same training data?
I have tried to debug this, but have not made any headway. Any ideas on how to proceed? I believe I am invoking everything correctly.
Here is a snippet of the code:
if ... |
H: Which algorithm Doc2Vec uses?
Like Word2vec is not a single algorithm but combination of two, namely, CBOW and Skip-Gram model; is Doc2Vec also a combination of any such algorithms? Or is it an algorithm in itself?
AI: Word2Vec is not a combination of two models, rather both are variants of word2vec. Similarly doc2... |
H: Cross-entropy loss explanation
Suppose I build a neural network for classification. The last layer is a dense layer with Softmax activation. I have five different classes to classify. Suppose for a single training example, the true label is [1 0 0 0 0] while the predictions be [0.1 0.5 0.1 0.1 0.2]. How would I cal... |
H: Python - Check if text is sentences?
So I have a scraper that gets articles. However, it doesn't always work properly. I want to get better at checking when it doesn't work. For example, the following is something like I want it to scrape:
Hello. This is a sequence of sentences that are put together. They don't h... |
H: Why do we pick random features in random forest
I understand that random forest is a stylized version of bagging of trees. We choose randomly data points as well as random features for constructing random forest.
But if we use just plain version of bagging by choosing only data points randomly then we have trees wh... |
H: Excel file merge with different headers but same data
I need to merge data from 1000s of excel files provided by different operations managers on productivity and other reports. The excel files have similarity of data but the headers are all custom since being different manager and different clients.
For example ma... |
H: Feature engineering while using neural networks
When doing Data Science, we concentrate on feature engineering first - check on correlations, imputations, tranformations etc.
Do we have to follow the same steps while feeding the inputs to a neural net? Or what should be the steps taken?
AI: If you are talking abo... |
H: Determine when entry/series of entries are outliers
A common question I face is this:
I have a stream of incoming data. Let's call it a vector of entries where each entry represents a value. As I'm getting this stream of entries that is getting added to the vector, I want to figure out if one of them is an outlier.... |
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