Questions marquées «multiclass-classification»

12
Combien de cellules LSTM dois-je utiliser?

Existe-t-il des règles générales (ou des règles réelles) concernant la quantité minimale, maximale et "raisonnable" de cellules LSTM que je devrais utiliser? Plus précisément, je me rapporte à BasicLSTMCell de TensorFlow et à la num_unitspropriété. Veuillez supposer que j'ai un problème de...

rnn machine-learning r predictive-modeling random-forest python language-model sentiment-analysis encoding machine-learning deep-learning neural-network dataset caffe classification xgboost multiclass-classification unbalanced-classes time-series descriptive-statistics python r clustering machine-learning python deep-learning tensorflow machine-learning python predictive-modeling probability scikit-learn svm machine-learning python classification gradient-descent regression research python neural-network deep-learning convnet keras python tensorflow machine-learning deep-learning tensorflow python r bigdata visualization rstudio pandas pyspark dataset time-series multilabel-classification machine-learning neural-network ensemble-modeling kaggle machine-learning linear-regression cnn convnet machine-learning tensorflow association-rules machine-learning predictive-modeling training model-selection neural-network keras deep-learning deep-learning convnet image-classification predictive-modeling prediction machine-learning python classification predictive-modeling scikit-learn machine-learning python random-forest sampling training recommender-system books python neural-network nlp deep-learning tensorflow python matlab information-retrieval search search-engine deep-learning convnet keras machine-learning python cross-validation sampling machine-learning
10
Quand choisir la régression linéaire ou l'arbre de décision ou la régression de forêt aléatoire? [fermé]

Fermé . Cette question doit être plus ciblée . Il n'accepte pas actuellement de réponses. Voulez-vous améliorer cette question? Mettez à jour la question pour qu'elle se concentre sur un seul problème en modifiant ce post . Fermé il y a 4 ans . Je travaille sur un projet et j'ai du mal à décider...

machine-learning algorithms random-forest linear-regression decision-trees machine-learning predictive-modeling forecast r clustering similarity data-mining dataset statistics text-mining text-mining data-cleaning data-wrangling machine-learning classification algorithms xgboost data-mining dataset dataset regression graphs svm unbalanced-classes cross-validation optimization hyperparameter genetic-algorithms visualization predictive-modeling correlation machine-learning predictive-modeling apache-spark statistics normalization apache-spark map-reduce r correlation confusion-matrix r data-cleaning classification terminology dataset image-classification machine-learning regression apache-spark machine-learning data-mining nlp parsing machine-learning dimensionality-reduction visualization clustering multiclass-classification evaluation unsupervised-learning machine-learning machine-learning data-mining supervised-learning unsupervised-learning machine-learning data-mining classification statistics predictive-modeling data-mining clustering python pandas machine-learning dataset data-cleaning data bigdata software-recommendation
10
Relation entre la convolution en mathématiques et CNN

J'ai lu l' explication de la convolution et je la comprends dans une certaine mesure. Quelqu'un peut-il m'aider à comprendre comment cette opération est liée à la convolution dans les réseaux neuronaux convolutionnels? Le filtre est-il une fonction gqui applique du

machine-learning neural-network deep-learning cnn convolution machine-learning ensemble-modeling machine-learning classification data-mining clustering machine-learning feature-selection convnet pandas graphs ipython machine-learning apache-spark multiclass-classification naive-bayes-classifier multilabel-classification machine-learning data-mining dataset data-cleaning data machine-learning data-mining statistics correlation machine-learning data-mining dataset data-cleaning data beginner career python r visualization machine-learning data-mining nlp stanford-nlp dataset linear-regression time-series correlation anomaly-detection ensemble-modeling data-mining machine-learning python data-mining recommender-system machine-learning cross-validation model-selection scoring prediction sequential-pattern-mining categorical-data python tensorflow image-recognition statistics machine-learning data-mining predictive-modeling data-cleaning preprocessing classification deep-learning tensorflow machine-learning algorithms data keras categorical-data reference-request loss-function classification logistic-regression apache-spark prediction naive-bayes-classifier beginner nlp word2vec vector-space-models scikit-learn decision-trees data programming