hashedml 0.0.1

Hash based machine learning

HashedML

A machine learning library that uses a different approach: string hashing (think hash tables) for classifying sequences.

Installation

PyPI (not available yet):

pip install -U hashedml

setup.py:

python setup.py build
python setup.py install

Classification

HashedML takes the simple fit(X, y) / predict(X) approach.

Example:

model = HashedML()
iris_data = open('iris.data').read().split('\n')
for i in iris_data:
    i = i.split(',')
    X = i[:-1]
    y = i[-1]
    model.fit(X, y)

iris_test = open('iris.test').read().split('\n')
for i in irist_test:
    i = i.split(',')
    X = i[:-1]
    y = i[-1]
    # use test() to get accuracy
    prediction = model.test(X, y)
    # -or: normally you don't have 'y'
    prediction = model.predict(X)

print('accuracy: {}%'.format(model.accuracy()*100))

Generative

HashedML can also generate data after learning.

Example:

from collections import deque
model = HashedML(nback=4, stm=True)
token_q = deque(maxlen=model.nback)
tokens = []

tokens = TextBlob(open('training.text').read()).tokens

# Learn
for i in tokens:
    token_q.append(i)
    if len(token_q) != model.nback:
        continue
    X = list(token_q)tq[:-1]
    y = list(token_q)tq[-1]
    model.fit(X, y)

# Generate
output = model.generate(
    ('What', 'is'),
    nwords=500,
    seperator=' '
)
print(output)

Variable X Input & Non-numerical X or Y

The X value can be of varying length/dimensions. For example, this is valid:

X = (
    (1, 2, 3),
    (1, 2),
    (1, 2, 3, 4),
)
# y can be of different data types
y  = (
    'y1',
    2.0,
    'foostring'
)

All data is converted to strings. This is conterintuitive and different than most machine learning libraries, but helps with working with variable X/y data.

Examples

% for i in test-data/*.test; do echo; echo -en "$i: "; data_file=$(echo $i|sed 's/.test/.data/g'); hashedml classify $data_file $i ; done

test-data/abalone.test: accuracy: 100.0%

test-data/allhypo.test: accuracy: 89.61%

test-data/anneal.test: accuracy: 82.0%

test-data/arrhythmia.test: accuracy: 100.0%

test-data/breast-cancer.test: accuracy: 100.0%

test-data/bupa.test: accuracy: 100.0%

test-data/glass.test: accuracy: 100.0%

test-data/iris.test: accuracy: 100.0%

test-data/long.test: accuracy: 100.0%

test-data/parkinsons_updrs.test: accuracy: 100.0%

test-data/soybean-large.test: accuracy: 97.87%

test-data/tic-tac-toe.test: accuracy: 100.0%