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from flask import Flask, request, jsonify, render_template
from flask_cors import CORS
from dataset.iris import iris
from opts import options
# using the iris data set for every algorithm
X, y = iris()
app = Flask(
__name__,
template_folder="templates",
)
CORS(
app=app,
origins="*",
)
@app.route("/", methods=["GET"])
def index():
return render_template("index.html")
@app.route("/neural-network", methods=["POST", "GET"])
def neural_network():
# parse arguments
algorithm = options["neural-network"]
args = request.json["arguments"]
result = algorithm(
X=X,
y=y,
args=args,
)
return jsonify(result)
@app.route("/kmeans-clustering", methods=["POST"])
def kmeans():
algorithm = options["kmeans-clustering"]
args = request.json["arguments"]
result = algorithm(
X=X,
y=y,
clusterer="kmeans-clustering",
args=args,
)
return jsonify(result)
if __name__ == "__main__":
app.run(debug=False)
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