title | layout |
---|---|
Notes on xgboost: Extreme Gradient Boosting Machine |
default |
- Computation in C++
- tree-based models
- easy to use, install, R/python interface
- Automatic parallel computation on a single Machine
import hashlib as hasher | |
import datetime as date | |
# Define what a Snakecoin block is | |
class Block: | |
def __init__(self, index, timestamp, data, previous_hash): | |
self.index = index | |
self.timestamp = timestamp | |
self.data = data | |
self.previous_hash = previous_hash |
import hashlib as hasher | |
class Block: | |
def __init__(self, index, timestamp, data, previous_hash): | |
self.index = index | |
self.timestamp = timestamp | |
self.data = data | |
self.previous_hash = previous_hash | |
self.hash = self.hash_block() | |
title | subtitle | layout |
---|---|---|
Notes from Statistical Learning Course |
via Stanford University Online |
default |
import sys | |
salesTotal = 0 | |
oldKey = None | |
for line in sys.stdin: | |
data = line.strip().split("\t") | |
if len(data) != 2: | |
# Something has gone wrong. Skip this line. | |
continue |