<commit_before>## Group:
  * What is the spike? More Visualizations,
                     Regressions ,
                     Clustering ,
                     PCA
  * Bic keeps getting better as we go up right now--look at more clusters!
  * Look at histograms of the x,y bics from last time
  * Sample 100 or 1000 samples and rerun x,y bic curve after sampling (run bic many times, take max for each k)
    because fragile to outliers
  * Look at the two kmeans center of clusters graphs in the z-layer. Better visualizations, which way do they trend?
  * Covariances from last hw as heat maps

## Emily:
  * Plot vector estimates on top of the z-layer cluster center graph to see if estimate makes sense.
  * Visualization of the "spike" (scatter plot)
  * Redo z-layer bics without setting random state (take max at each k)
  * Work off of jay's gradient of density estimate (not using uniques), compare the two
  * Visualization of clustering after running the bic curve for higher ks (kmeans)
  * In the spike:
   * Min/Max x-value
   * Min/Max y-value
   * Min/Max z-value
   * Max number of synapses at one point
   * Point at which max number of synpases occurs

## Bijan:
### 5 solo things hw week 4/4/2016
#### 1) Overlay the scatterplot and vector graphs to find relationships - they seemed to correlate.
#### 2) Find the direction between cluster centers per each z value, plot them all together and compare.
#### 3) Run what I did last week, creating direction of increasing density, using # of partitions as a hyperparameter. Compare data across # of partitions (in x, y, z).
#### 4) From the BIC curves generated last week, analyze the data from the z values that behaved differently (bend at 4 instead of 3). Plot histograms + cluster.
#### 5) Elastic net regression on predicting synapses from xyz data for each z value, especially the ones that behaved differently earlier.

## Akash:

## Jay:
<commit_msg>cleaned up formatting<commit_after>## Group:
  * What is the spike? More Visualizations,
                     Regressions ,
                     Clustering ,
                     PCA
  * Bic keeps getting better as we go up right now--look at more clusters!
  * Look at histograms of the x,y bics from last time
  * Sample 100 or 1000 samples and rerun x,y bic curve after sampling (run bic many times, take max for each k)
    because fragile to outliers
  * Look at the two kmeans center of clusters graphs in the z-layer. Better visualizations, which way do they trend?
  * Covariances from last hw as heat maps

## Emily:
  * Plot vector estimates on top of the z-layer cluster center graph to see if estimate makes sense.
  * Visualization of the "spike" (scatter plot)
  * Redo z-layer bics without setting random state (take max at each k)
  * Work off of jay's gradient of density estimate (not using uniques), compare the two
  * Visualization of clustering after running the bic curve for higher ks (kmeans)
  * In the spike:
   * Min/Max x-value
   * Min/Max y-value
   * Min/Max z-value
   * Max number of synapses at one point
   * Point at which max number of synpases occurs

## Bijan:
#### 5 solo things hw week 4/4/2016
  * Overlay the scatterplot and vector graphs to find relationships - they seemed to correlate.
  * Find the direction between cluster centers per each z value, plot them all together and compare.
  * Run what I did last week, creating direction of increasing density, using # of partitions as a hyperparameter. Compare data across # of partitions (in x, y, z).
  * From the BIC curves generated last week, analyze the data from the z values that behaved differently (bend at 4 instead of 3). Plot histograms + cluster.
  * Elastic net regression on predicting synapses from xyz data for each z value, especially the ones that behaved differently earlier.

## Akash:

## Jay:

{'fraction_non_alphanumeric': 0.060203283815480846, 'fraction_numerical': 0.009642950221527235, 'mean_word_length': 3.2083333333333335, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '4005789', 'n_tokens_mistral': 1091, 'n_tokens_neox': 982, 'n_words': 569}