What's the meaning of dimensionality and what is it for this data?
2015年5月5日 · I've been told that dimensionality is usually referred to attributes or columns of the dataset. But in this case, does it include Class1 and Class2? and does dimensionality mean, …
What should you do if you have too many features in your dataset ...
2020年8月17日 · Whereas dimensionality reduction removes unnecessary/useless data that generates noise. My main question is, if excessive features in a dataset could cause overfitting …
Variational Autoencoder − Dimension of the latent space
What do you call a latent space here? The dimensionality of the layer that outputs means and deviations, or the layer that immediately precedes that? It sounds like you're talking about the …
Curse of dimensionality- does cosine similarity work better and if …
2018年4月19日 · When working with high dimensional data, it is almost useless to compare data points using euclidean distance - this is the curse of dimensionality. However, I have read that …
dimensionality reduction - Relationship between SVD and PCA.
2015年1月22日 · However, it can also be performed via singular value decomposition (SVD) of the data matrix $\mathbf X$. How does it work? What is the connection between these two …
machine learning - What is a latent space? - Cross Validated
2019年12月27日 · In machine learning I've seen people using high dimensional latent space to denote a feature space induced by some non-linear data transformation which increases the …
Does SVM suffer from curse of high dimensionality? If no, Why?
2020年8月23日 · While I know that some of the classification techniques such as k-nearest neighbour classifier suffer from the curse of high dimensionality, I wonder does the same apply …
clustering - Which dimensionality reduction technique works well …
2020年9月10日 · Which dimensionality reduction technique works well for BERT sentence embeddings? Ask Question Asked 4 years, 8 months ago Modified 3 years, 5 months ago
Intuitive explanation of how UMAP works, compared to t-SNE
2019年4月12日 · I have a PhD in molecular biology. My studies recently started to involve high dimensional data analysis. I got the idea of how t-SNE works (thanks to a StatQuest video on …
Can the elbow method be used in PCA (Principal ... - Cross Validated
2025年5月16日 · I’m wondering if a similar technique can be applied to PCA for dimensionality reduction. Specifically, can we use an "elbow" in the explained variance plot to determine the …