Written with Python Flask Framework, if you want to port to PHP or Node.js, just change the templates in app/templates
folder.
- SSH Running from Mac or Linux console, use putty if you are on Windows:
Written with Python Flask Framework, if you want to port to PHP or Node.js, just change the templates in app/templates
folder.
Engedit Manual | |
=========== | |
Written with Python Flask Framework, if you want to port to PHP or Node.js, just change the templates in `app/templates` folder. | |
How to run the website | |
------------------------ |
2norm | |
![enter image description here][1] | |
kl-divergence | |
![enter image description here][4] | |
errorbars | |
![enter image description here][2] | |
errors |
New Idea of the fast forward random walk | |
================== | |
Definition | |
---------- | |
The fast forward random walk works as follows: it try to avoid coming back to the former clique. | |
* Denote the rrandom walk's 2-lag history as $(u_2, v_2), (u_1, v_1)$ |
# Error Bar plot for distance estimation | |
### Steps | |
* Choose an initial node | |
* Denote other nodes' attributes $d(v)$ as the shortest path's length from $v$ to the initial node (distance to the initial node) | |
* Estimate $D = \sum\pi(v)d(v)$, where $\pi(v) = \frac{k_v}{2|E|}$ | |
* Useful and convenient, because we can simply apply the mean function to the sample to get unbiased estimation of $\hat{D}$. |
# 1204 2norm avgError KL | |
* 2-Norm and KL-divergence are based on one vertical array's distribution | |
* One of the average error is estimated using sliding window | |
## 2-Norm | |
![enter image description here][1] | |
## Average Error (Non Sliding window) |
# 1204 2norm avgError KL | |
* 2-Norm and KL-divergence are based on one vertical array's distribution | |
* One of the average error is estimated using sliding window | |
## 2-Norm | |
![enter image description here][1] | |
## Average Error (Non Sliding window) | |
![enter image description here][2] |
# 1204 2norm avgError KL | |
* 2-Norm and KL-divergence are based on one vertical array's distribution | |
* One of the average error is estimated using sliding window | |
## 2-Norm | |
![enter image description here][1] | |
## Average Error (Sliding window) | |
![enter image description here][2] |
# Facebook0 dataset | |
## 2Norm-large | |
![2Norm-large][1] | |
## 2Norm-small | |
![enter image description here][2] | |
## AvgError-large |
# Facebook0 dataset | |
## 2Norm-large | |
![2Norm-large][1] | |
## 2Norm-small | |
![enter image description here][2] | |
## AvgError-large |