engine update
This commit is contained in:
parent
62e91b264e
commit
08ee963d86
1
.gitignore
vendored
Normal file
1
.gitignore
vendored
Normal file
@ -0,0 +1 @@
|
||||
__pycache__
|
||||
112
engine.py
112
engine.py
@ -1,73 +1,73 @@
|
||||
from simpful import *
|
||||
|
||||
FS = FuzzySystem(show_banner=False)
|
||||
def fuzzy_system(release_year_param, runtime_param, seasons_param, genres_param, emotions_param):
|
||||
|
||||
# Define fuzzy sets for the variable
|
||||
# RELEASE_YEAR
|
||||
release_year_newer = TriangleFuzzySet(-20, -20, 0, term="newer")
|
||||
release_year_similar = TriangleFuzzySet(-20, 0, 20, term="similar")
|
||||
release_year_older = TriangleFuzzySet(0, 20, 20, term="older")
|
||||
FS = FuzzySystem(show_banner=False)
|
||||
|
||||
FS.add_linguistic_variable("RELEASE_YEAR",
|
||||
LinguisticVariable([release_year_newer, release_year_similar, release_year_older],
|
||||
universe_of_discourse=[-136, 136]))
|
||||
# Define fuzzy sets for the variable
|
||||
# RELEASE_YEAR
|
||||
release_year_newer = TriangleFuzzySet(-20, -20, 0, term="newer")
|
||||
release_year_similar = TriangleFuzzySet(-20, 0, 20, term="similar")
|
||||
release_year_older = TriangleFuzzySet(0, 20, 20, term="older")
|
||||
|
||||
# RUNTIME
|
||||
runtime_shorter = TriangleFuzzySet(-90, -90, 0, term="shorter")
|
||||
runtime_similar = TriangleFuzzySet(-90, 0, 90, term="similar")
|
||||
runtime_longer = TriangleFuzzySet(0, 90, 90, term="longer")
|
||||
FS.add_linguistic_variable("RELEASE_YEAR",
|
||||
LinguisticVariable([release_year_newer, release_year_similar, release_year_older],
|
||||
universe_of_discourse=[-136, 136]))
|
||||
|
||||
FS.add_linguistic_variable("RUNTIME", LinguisticVariable([runtime_shorter, runtime_similar, runtime_longer],
|
||||
universe_of_discourse=[-476, 476]))
|
||||
# RUNTIME
|
||||
runtime_shorter = TriangleFuzzySet(-90, -90, 0, term="shorter")
|
||||
runtime_similar = TriangleFuzzySet(-90, 0, 90, term="similar")
|
||||
runtime_longer = TriangleFuzzySet(0, 90, 90, term="longer")
|
||||
|
||||
# SEASONS
|
||||
seasons_less = TriangleFuzzySet(-5, -5, 0, term="less")
|
||||
seasons_similar = TriangleFuzzySet(-5, 0, 5, term="similar")
|
||||
seasons_more = TriangleFuzzySet(0, 5, 5, term="more")
|
||||
FS.add_linguistic_variable("RUNTIME", LinguisticVariable([runtime_shorter, runtime_similar, runtime_longer],
|
||||
universe_of_discourse=[-476, 476]))
|
||||
|
||||
FS.add_linguistic_variable("SEASONS", LinguisticVariable([seasons_less, seasons_similar, seasons_more],
|
||||
universe_of_discourse=[-84, 84]))
|
||||
# SEASONS
|
||||
seasons_less = TriangleFuzzySet(-5, -5, 0, term="less")
|
||||
seasons_similar = TriangleFuzzySet(-5, 0, 5, term="similar")
|
||||
seasons_more = TriangleFuzzySet(0, 5, 5, term="more")
|
||||
|
||||
# GENRES
|
||||
genres_different = TriangleFuzzySet(0, 0, 0.5, term="different")
|
||||
genres_similar = TriangleFuzzySet(0, 0.5, 1, term="similar")
|
||||
genres_same = TriangleFuzzySet(0.5, 1, 1, term="same")
|
||||
FS.add_linguistic_variable("SEASONS", LinguisticVariable([seasons_less, seasons_similar, seasons_more],
|
||||
universe_of_discourse=[-84, 84]))
|
||||
|
||||
FS.add_linguistic_variable("GENRES", LinguisticVariable([genres_different, genres_similar, genres_same],
|
||||
universe_of_discourse=[0, 1]))
|
||||
# GENRES
|
||||
genres_different = TriangleFuzzySet(0, 0, 0.5, term="different")
|
||||
genres_similar = TriangleFuzzySet(0, 0.5, 1, term="similar")
|
||||
genres_same = TriangleFuzzySet(0.5, 1, 1, term="same")
|
||||
|
||||
# EMOTIONS
|
||||
emotions_different = TriangleFuzzySet(0, 0, 0.5, term="different")
|
||||
emotions_similar = TriangleFuzzySet(0, 0.5, 1, term="similar")
|
||||
emotions_same = TriangleFuzzySet(0.5, 1, 1, term="same")
|
||||
FS.add_linguistic_variable("GENRES", LinguisticVariable([genres_different, genres_similar, genres_same],
|
||||
universe_of_discourse=[0, 1]))
|
||||
|
||||
FS.add_linguistic_variable("EMOTIONS", LinguisticVariable([emotions_different, emotions_similar, emotions_same],
|
||||
universe_of_discourse=[0, 1]))
|
||||
# EMOTIONS
|
||||
emotions_different = TriangleFuzzySet(0, 0, 0.5, term="different")
|
||||
emotions_similar = TriangleFuzzySet(0, 0.5, 1, term="similar")
|
||||
emotions_same = TriangleFuzzySet(0.5, 1, 1, term="same")
|
||||
|
||||
# RECOMMENDATION
|
||||
low_recommendation = TriangleFuzzySet(0, 0, 50, term="low_recommendation")
|
||||
medium_recommendation = TriangleFuzzySet(0, 50, 100, term="medium_recommendation")
|
||||
high_recommendation = TriangleFuzzySet(0, 100, 100, term="high_recommendation")
|
||||
FS.add_linguistic_variable("RECOMMENDATION",
|
||||
LinguisticVariable([low_recommendation, medium_recommendation, high_recommendation],
|
||||
universe_of_discourse=[0, 200]))
|
||||
FS.add_linguistic_variable("EMOTIONS", LinguisticVariable([emotions_different, emotions_similar, emotions_same],
|
||||
universe_of_discourse=[0, 1]))
|
||||
|
||||
# RULES
|
||||
RULE1 = "IF (RELEASE_YEAR IS older) AND (RUNTIME IS longer) AND (SEASONS IS more) THEN (RECOMMENDATION IS low_recommendation)"
|
||||
RULE2 = "IF (EMOTIONS IS different) AND (GENRES IS different) THEN (RECOMMENDATION IS low_recommendation)"
|
||||
RULE3 = "IF (RELEASE_YEAR IS newer) AND (RUNTIME IS similar) AND (SEASONS IS less) THEN (RECOMMENDATION IS medium_recommendation)"
|
||||
RULE4 = "IF (EMOTIONS IS similar) AND (GENRES IS similar) THEN (RECOMMENDATION IS medium_recommendation)"
|
||||
RULE5 = "IF (RELEASE_YEAR IS similar) AND (RUNTIME IS similar) AND (SEASONS IS similar) AND (EMOTIONS IS same) AND (GENRES IS same) THEN (RECOMMENDATION IS high_recommendation)"
|
||||
# Z regułami trzeba eksperymentować, można porównywać ze scorem dla sprawdzania skuteczności
|
||||
# RECOMMENDATION
|
||||
low_recommendation = TriangleFuzzySet(0, 0, 50, term="low_recommendation")
|
||||
medium_recommendation = TriangleFuzzySet(0, 50, 100, term="medium_recommendation")
|
||||
high_recommendation = TriangleFuzzySet(0, 100, 100, term="high_recommendation")
|
||||
FS.add_linguistic_variable("RECOMMENDATION",
|
||||
LinguisticVariable([low_recommendation, medium_recommendation, high_recommendation],
|
||||
universe_of_discourse=[0, 200]))
|
||||
|
||||
FS.add_rules([RULE1, RULE2, RULE3, RULE4, RULE5])
|
||||
# # RULES
|
||||
# RULE1 = "IF (RELEASE_YEAR IS older) AND (RUNTIME IS longer) AND (SEASONS IS more) THEN (RECOMMENDATION IS low_recommendation)"
|
||||
# RULE2 = "IF (EMOTIONS IS different) AND (GENRES IS different) THEN (RECOMMENDATION IS low_recommendation)"
|
||||
# RULE3 = "IF (RELEASE_YEAR IS newer) AND (RUNTIME IS similar) AND (SEASONS IS less) THEN (RECOMMENDATION IS medium_recommendation)"
|
||||
# RULE4 = "IF (EMOTIONS IS similar) AND (GENRES IS similar) THEN (RECOMMENDATION IS medium_recommendation)"
|
||||
# RULE5 = "IF (RELEASE_YEAR IS similar) AND (RUNTIME IS similar) AND (SEASONS IS similar) AND (EMOTIONS IS same) AND (GENRES IS same) THEN (RECOMMENDATION IS high_recommendation)"
|
||||
# # Z regułami trzeba eksperymentować, można porównywać ze scorem dla sprawdzania skuteczności
|
||||
|
||||
# FS.set_variable("RELEASE_YEAR", -12.0)
|
||||
# FS.set_variable("RUNTIME", -10.0)
|
||||
# FS.set_variable("SEASONS", -2.0)
|
||||
# FS.set_variable("GENRES", 50.0)
|
||||
# FS.set_variable("EMOTIONS", 1.0)
|
||||
#
|
||||
# print(FS.inference(["RECOMMENDATION"]))
|
||||
# RULES
|
||||
RULE1 = f"IF (NOT (RELEASE_YEAR IS {release_year_param})) AND (NOT (RUNTIME IS {runtime_param})) AND (NOT (SEASONS IS {seasons_param})) THEN (RECOMMENDATION IS low_recommendation)"
|
||||
RULE2 = f"IF (NOT (EMOTIONS IS {emotions_param})) AND (NOT (GENRES IS {genres_param})) THEN (RECOMMENDATION IS low_recommendation)"
|
||||
RULE3 = f"IF (NOT (RELEASE_YEAR IS {release_year_param})) AND (RUNTIME IS {runtime_param}) AND (NOT (SEASONS IS {seasons_param})) THEN (RECOMMENDATION IS medium_recommendation)"
|
||||
RULE4 = f"IF (EMOTIONS IS {emotions_param}) AND (GENRES IS {genres_param}) THEN (RECOMMENDATION IS medium_recommendation)"
|
||||
RULE5 = f"IF (RELEASE_YEAR IS {release_year_param}) AND (RUNTIME IS {runtime_param}) AND (SEASONS IS {seasons_param}) AND (EMOTIONS IS {emotions_param}) AND (GENRES IS {genres_param}) THEN (RECOMMENDATION IS high_recommendation)"
|
||||
FS.add_rules([RULE1, RULE2, RULE3, RULE4, RULE5])
|
||||
|
||||
# FS.produce_figure(outputfile='visualize_terms.pdf')
|
||||
return FS
|
||||
|
||||
4
main.py
4
main.py
@ -16,7 +16,7 @@ from fastapi import FastAPI
|
||||
from scipy.spatial.distance import cosine
|
||||
from sklearn.preprocessing import MultiLabelBinarizer
|
||||
|
||||
from engine import FS
|
||||
from engine import fuzzy_system
|
||||
|
||||
app = FastAPI()
|
||||
data = pd.DataFrame()
|
||||
@ -28,6 +28,8 @@ def inference(first: pandas.core.series.Series, second_id: str, df=None):
|
||||
else:
|
||||
second = data.loc[second_id]
|
||||
|
||||
FS = fuzzy_system(release_year_param='similar', runtime_param='similar', seasons_param='similar', genres_param='same', emotions_param='same')
|
||||
|
||||
year_diff = int(first['release_year'] - second['release_year'])
|
||||
FS.set_variable('RELEASE_YEAR', year_diff)
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user